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Development of an objective method for the comparison of fired projectiles using an air pistol as a template
Get PDFStrathclyde theses - ask staff. Thesis no. : T14495The ability to objectify ballistic evidence is a challenge faced by firearms examiners around the world. A number of researchers are trying to improve bullet-identification systems to address the deficiencies in this regard and which were detailed within the National Academy of Sciences report (2009). Bullet to bullet comparisons have largely relied on the supposition that the rifling marks within the barrel of a weapon have class characteristics that identify a weapon type and individual characteristics that identify a specific weapon. Such characteristics are impressed onto projectiles when they are fired through a particular weapon and an examination of specific regions displaying striated marks on the projectiles allows for identification and comparison to be undertaken. This premise has been the foundation for comparative firearms examination for many decades. In many cases only small portions of striated regions of the projectile are examined and the process is essentially subjective. More recently focus has turned to making use of more sophisticated imaging modalities to view entire regions of the projectile and the development of automated systems for the comparison of the topographical surfaces recorded. Projectiles from a fired series of 609 pellets were examined using an Alicona infinite focus microscope. A mathematical methodology was developed to pre-process the resultant topographical maps generating point data for comparison. Comparisons between different data sets were undertaken using chemometric techniques (principal component analysis, hierarchical cluster analysis and linear discriminant analysis) to assess (1) the repeatability and reproducibility of the method, (2) the variability of land engraved areas (LEAs) in repetitively fired projectiles over a series of test fires, (3) the ability of the developed method to distinguish between different classes of weapons (pistols and rifles) and weapons within the same class (rifles) and (4) the ability of the method to correctly associate distorted projectiles to the weapon that fired them.The developed objective method still requires an operator to identify the LEAs to be scanned; however the mathematical alignments were objectively achieved. The discrimination of weapons by class was achieved although weapons within the same class could not be easily separated from each other. The LEAs on a single projectile varied in terms of distinction from each other and, while there was some variation with use of the same weapon over time, this was not pronounced. Generally the LEAs with more distinguishing features across the entire region created a better discriminating surface and in particular facilitated the correct association for distorted projectiles.The ability to objectify ballistic evidence is a challenge faced by firearms examiners around the world. A number of researchers are trying to improve bullet-identification systems to address the deficiencies in this regard and which were detailed within the National Academy of Sciences report (2009). Bullet to bullet comparisons have largely relied on the supposition that the rifling marks within the barrel of a weapon have class characteristics that identify a weapon type and individual characteristics that identify a specific weapon. Such characteristics are impressed onto projectiles when they are fired through a particular weapon and an examination of specific regions displaying striated marks on the projectiles allows for identification and comparison to be undertaken. This premise has been the foundation for comparative firearms examination for many decades. In many cases only small portions of striated regions of the projectile are examined and the process is essentially subjective. More recently focus has turned to making use of more sophisticated imaging modalities to view entire regions of the projectile and the development of automated systems for the comparison of the topographical surfaces recorded. Projectiles from a fired series of 609 pellets were examined using an Alicona infinite focus microscope. A mathematical methodology was developed to pre-process the resultant topographical maps generating point data for comparison. Comparisons between different data sets were undertaken using chemometric techniques (principal component analysis, hierarchical cluster analysis and linear discriminant analysis) to assess (1) the repeatability and reproducibility of the method, (2) the variability of land engraved areas (LEAs) in repetitively fired projectiles over a series of test fires, (3) the ability of the developed method to distinguish between different classes of weapons (pistols and rifles) and weapons within the same class (rifles) and (4) the ability of the method to correctly associate distorted projectiles to the weapon that fired them.The developed objective method still requires an operator to identify the LEAs to be scanned; however the mathematical alignments were objectively achieved. The discrimination of weapons by class was achieved although weapons within the same class could not be easily separated from each other. The LEAs on a single projectile varied in terms of distinction from each other and, while there was some variation with use of the same weapon over time, this was not pronounced. Generally the LEAs with more distinguishing features across the entire region created a better discriminating surface and in particular facilitated the correct association for distorted projectiles
Computational modelling and design of bioinspired silica materials
No full textThe use of bio-inspired methods for production of mesoporous silicas could lead to significant improvements in the synthetic conditions at which these materials are traditionally produced, removing the need for strong pH as well as high temperatures and pressures, and opening the way for milder treatments for template removal. However, due to the complexity of these systems, with many processes occurring simultaneously and high dependence on the specific synthetic conditions,obtaining a detailed description of their mechanism of formation based only on experimental methods is often very difficult. To overcome this difficulty, simulations methods, particularly molecular dynamics, have been developed and used to shed some light into this complex but fascinating problem.In the present thesis, the processes underlying the synthesis of bio-inspired silica materials are investigated at computational level by means of a multi-scale approach.This methodology has two major advantages: it enables to explore longer time and length scales, beyond the current limit of atomistic simulations, while allowing to maintain realism at the lower resolution levels, which are calibrated to match properties obtained at higher levels of theory.The work can be divided into two main parts. The first part aims to provide more insight into the synthesis of two early examples of bio-inspired materials(HMS and MSU-V), by means of a combination of atomistic and coarse-grained simulations. HMS and MSU-V materials share some common characteristics: they are both synthesised using amine surfactants as templates and a neutral templating route has been proposed to explain their formation. By simulating their synthesis at different pH values, it was possible to show that charged species are necessary to promote mesophase formation (disordered packing of rod-like micelles for HMS materials and lamellar structures for HMS). In both systems, in fact, neutral species produced phase separation of the templating materials into an unstructured and non-porous phase, and the lack of interactions with silicates indicates that these conditions cannot lead to structural organisation. Hence, molecular dynamics simulations reveal that, similarly to other mesoporous silicas and contrary to what has been previously hypothesised, charge matching interactions rather than hydrogen bonds are responsible for the self-assemble this class of materials. This knowledge is fundamental to provide further control over the properties of these solids and target their design for specific applications.In the second part, atomistic simulations are used to help elucidate the mechanism of template removal from a bio-inspired silica material by solvent extraction.This revealed that mild post-synthetic acid treatments allow to remove the templating additive by reducing, and eventually switching off, its interaction with the silica material. In agreement with experimental findings, which show that the majority of the additive is removed between pH 5 and 4, simulations indicate that at pH below 4.2 thermal fluctuations are sufficient to cause widespread release of the template. This result suggests that molecular simulations can be used as a simple and inexpensive tool for choosing appropriate solvents and experimental conditions in the material purification processes.The use of bio-inspired methods for production of mesoporous silicas could lead to significant improvements in the synthetic conditions at which these materials are traditionally produced, removing the need for strong pH as well as high temperatures and pressures, and opening the way for milder treatments for template removal. However, due to the complexity of these systems, with many processes occurring simultaneously and high dependence on the specific synthetic conditions,obtaining a detailed description of their mechanism of formation based only on experimental methods is often very difficult. To overcome this difficulty, simulations methods, particularly molecular dynamics, have been developed and used to shed some light into this complex but fascinating problem.In the present thesis, the processes underlying the synthesis of bio-inspired silica materials are investigated at computational level by means of a multi-scale approach.This methodology has two major advantages: it enables to explore longer time and length scales, beyond the current limit of atomistic simulations, while allowing to maintain realism at the lower resolution levels, which are calibrated to match properties obtained at higher levels of theory.The work can be divided into two main parts. The first part aims to provide more insight into the synthesis of two early examples of bio-inspired materials(HMS and MSU-V), by means of a combination of atomistic and coarse-grained simulations. HMS and MSU-V materials share some common characteristics: they are both synthesised using amine surfactants as templates and a neutral templating route has been proposed to explain their formation. By simulating their synthesis at different pH values, it was possible to show that charged species are necessary to promote mesophase formation (disordered packing of rod-like micelles for HMS materials and lamellar structures for HMS). In both systems, in fact, neutral species produced phase separation of the templating materials into an unstructured and non-porous phase, and the lack of interactions with silicates indicates that these conditions cannot lead to structural organisation. Hence, molecular dynamics simulations reveal that, similarly to other mesoporous silicas and contrary to what has been previously hypothesised, charge matching interactions rather than hydrogen bonds are responsible for the self-assemble this class of materials. This knowledge is fundamental to provide further control over the properties of these solids and target their design for specific applications.In the second part, atomistic simulations are used to help elucidate the mechanism of template removal from a bio-inspired silica material by solvent extraction.This revealed that mild post-synthetic acid treatments allow to remove the templating additive by reducing, and eventually switching off, its interaction with the silica material. In agreement with experimental findings, which show that the majority of the additive is removed between pH 5 and 4, simulations indicate that at pH below 4.2 thermal fluctuations are sufficient to cause widespread release of the template. This result suggests that molecular simulations can be used as a simple and inexpensive tool for choosing appropriate solvents and experimental conditions in the material purification processes
New algorithms for enhancing ultrasonic NDE of difficult materials
Get PDFIn Non-Destructive Evaluation (NDE) inspection, a range of materials exist that exhibit a heterogeneous or acoustically scattering microstructure, for example austenitic steels and Inconel alloys, and are used extensively across many industrial sectors. When inspected using conventional ultrasound techniques, defect signals are significantly corrupted by noise from randomly distributed scatterer associated with the material microstructure. In some cases, even defects that are much larger than the grain size distribution in the microstructure can be difficult to detect. This Thesis presents an investigation into the development of new algorithms to suppress backscattering noise in the received ultrasonic echoes associated with both individual transducers and phased arrays. Using the fact that structural noise in these difficult materials is frequency coherent, frequency diversity based techniques like the well-known Split Spectrum Processing have been developed. However, conventional algorithms are either ineffective or sensitive to the variations of material characteristics, especially when the signal to noise ratio (SNR) is low. A frequency diversity based technique, Moving Bandwidth Split Spectrum Processing (MB-SSP), has been developed, which is less influenced by material characteristics. MB-SSP first selects an ascending series of frequency bands and a trace is reconstructed for each selected band in which a defect is present: this occurs when all frequency components are in uniform sign. Combining all reconstructed signals through averaging gives a probability profile of potential defect positions. A range of supervised machine learning techniques has also been employed to further improve detect capability, if the pre-acquired training data is available. Instead of investigating the structure and pattern of the spectrum of an individual echo, the proposed method focuses on the distinction between the ensembles of defect signals and clutter noise. A training process is used to establish the statistical analysis, based on which a hypothesis test is then applied to the received echoes to indicate defects. The approach is designed to be adaptive to the material microstructure and characteristics due to the statistical training aspect of the technique. The concept of applying clustering algorithms to further reduce the influence of artefact noise remaining in A-scan data after processing by MB-SSP or a conventional defect detection algorithm is also discussed. The segmental signals that potentially contain defects in the processed A-scans are clustered into groups. The distinction and similarity between each group and the ensemble of randomly selected noise segments can be observed by applying a classification algorithm. Each class will then be labelled as either a 'legitimate reflector' or 'artefact' based on this observation and the expected probability of detection (PoD) and the probability of false alarm (PFA) determined. Finally, the developed A-scan based noise reduction algorithms have been extended into phased array imaging. Here the techniques are applied to the raw Full Matrix Capture (FMC) datasets prior to processing by an appropriate imaging algorithm. Total Focusing Method (TFM) and the focused B-scan imaging is applied to both standard and pre-processed FMC datasets on both simulated data and experimental data from coarse-grained materials. Importantly, the background noise is significantly suppressed in every case using the pre-processed FMC data.In Non-Destructive Evaluation (NDE) inspection, a range of materials exist that exhibit a heterogeneous or acoustically scattering microstructure, for example austenitic steels and Inconel alloys, and are used extensively across many industrial sectors. When inspected using conventional ultrasound techniques, defect signals are significantly corrupted by noise from randomly distributed scatterer associated with the material microstructure. In some cases, even defects that are much larger than the grain size distribution in the microstructure can be difficult to detect. This Thesis presents an investigation into the development of new algorithms to suppress backscattering noise in the received ultrasonic echoes associated with both individual transducers and phased arrays. Using the fact that structural noise in these difficult materials is frequency coherent, frequency diversity based techniques like the well-known Split Spectrum Processing have been developed. However, conventional algorithms are either ineffective or sensitive to the variations of material characteristics, especially when the signal to noise ratio (SNR) is low. A frequency diversity based technique, Moving Bandwidth Split Spectrum Processing (MB-SSP), has been developed, which is less influenced by material characteristics. MB-SSP first selects an ascending series of frequency bands and a trace is reconstructed for each selected band in which a defect is present: this occurs when all frequency components are in uniform sign. Combining all reconstructed signals through averaging gives a probability profile of potential defect positions. A range of supervised machine learning techniques has also been employed to further improve detect capability, if the pre-acquired training data is available. Instead of investigating the structure and pattern of the spectrum of an individual echo, the proposed method focuses on the distinction between the ensembles of defect signals and clutter noise. A training process is used to establish the statistical analysis, based on which a hypothesis test is then applied to the received echoes to indicate defects. The approach is designed to be adaptive to the material microstructure and characteristics due to the statistical training aspect of the technique. The concept of applying clustering algorithms to further reduce the influence of artefact noise remaining in A-scan data after processing by MB-SSP or a conventional defect detection algorithm is also discussed. The segmental signals that potentially contain defects in the processed A-scans are clustered into groups. The distinction and similarity between each group and the ensemble of randomly selected noise segments can be observed by applying a classification algorithm. Each class will then be labelled as either a 'legitimate reflector' or 'artefact' based on this observation and the expected probability of detection (PoD) and the probability of false alarm (PFA) determined. Finally, the developed A-scan based noise reduction algorithms have been extended into phased array imaging. Here the techniques are applied to the raw Full Matrix Capture (FMC) datasets prior to processing by an appropriate imaging algorithm. Total Focusing Method (TFM) and the focused B-scan imaging is applied to both standard and pre-processed FMC datasets on both simulated data and experimental data from coarse-grained materials. Importantly, the background noise is significantly suppressed in every case using the pre-processed FMC data
Structural health monitoring of marine structures by using inverse finite element method
No full textStructural health monitoring (SHM) is a process aimed at providing accurate and real-time information concerning structural condition and performance. SHM is a very important discipline in the areas of civil, aerospace, and marine engineering because the utilization of SHM allows us to increase both human and environmental safety in conjunction with reduction in direct economic losses. A key component of the SHM process is real-time reconstruction of a structure's three-dimensional displacement and stress fields using a network of in situ strain sensors and measured strains, which is commonly referred to as "shape and stress sensing". The inverse finite element method (iFEM) is a revolutionary shape- and stress-sensing methodology shown to be fast, accurate, and robust for usage as a part of SHM systems. In the present thesis, the general framework of iFEM, i.e., least-squares variational principle, is adopted to develop unconventional and more effective shape- and stress-sensing techniques, with focus on general engineering structures and marine structures in particular. Firstly, the original iFEM formulation for plate and shell structures, developed on the basis of first-order shear deformation theory, is summarized. Then, this formulation is utilized to develop a new four-node quadrilateral inverse-shell element, iQS4, which further extends the practical utility of iFEM for shape sensing of large-scale structures including marine structures. Various numerical examples are presented and it is demonstrated that the iQS4 formulation is robust with respect to the membrane- and shear-locking phenomena. Moreover, the iFEM/iQS4 methodology is applied to various types of marine structures including a stiffened plate, a chemical tanker, and a container ship. To simulate experimentally measured strains and to establish reference displacements, a coupled hydrodynamic and high-fidelity finite element analyses are performed. Utilizing the simulated strain-sensor strains, iFEM analysis of each marine structure is performed. As a result, the optimum locations of the on-board strain sensors are determined for each marine structure.;Furthermore, a novel isogeometric Kirchhoff-Love inverse-shell element (iKLS) for more accurate shape-sensing analysis of curved/complex shell structures is presented. The new formulation employs the iFEM as a general framework and the non-uniform rational B-splines (NURBS) as the discretization technology for both structural geometry and displacement domain. Therefore, this new formulation couples the concept of isogeometric analysis with iFEM methodology and creates an innovative "isogeometric iFEM formulation". The superior shape-sensing capability of the isogeometric iFEM formulation (i.e., iKLS) is demonstrated for curved shell structures when using low-fidelity discretizations with few strain sensors. Finally, an improved iFEM formulation for dealing with shape and stress sensing of multilayered composite and sandwich plate/shell structures is described. The present iFEM formulation is based upon the minimization of a weighted-least-squares functional that uses the complete set of strain measures of refined zigzag theory (RZT). A new three-node inverse-shell element, i3-RZT, is developed based on the enhanced iFEM formulation. Various validation and demonstration problems are solved to examine the precision of the iFEM/i3-RZT methodology. The numerical results demonstrate the superior accuracy and robustness of the i3-RZT element for performing accurate shape and stress sensing of complex composite structures. In conclusion, all proposed iFEM frameworks are computationally efficient, accurate, and powerful, hence they can be helpful for shape sensing and SHM of general engineering structures, especially of marine structures.Structural health monitoring (SHM) is a process aimed at providing accurate and real-time information concerning structural condition and performance. SHM is a very important discipline in the areas of civil, aerospace, and marine engineering because the utilization of SHM allows us to increase both human and environmental safety in conjunction with reduction in direct economic losses. A key component of the SHM process is real-time reconstruction of a structure's three-dimensional displacement and stress fields using a network of in situ strain sensors and measured strains, which is commonly referred to as "shape and stress sensing". The inverse finite element method (iFEM) is a revolutionary shape- and stress-sensing methodology shown to be fast, accurate, and robust for usage as a part of SHM systems. In the present thesis, the general framework of iFEM, i.e., least-squares variational principle, is adopted to develop unconventional and more effective shape- and stress-sensing techniques, with focus on general engineering structures and marine structures in particular. Firstly, the original iFEM formulation for plate and shell structures, developed on the basis of first-order shear deformation theory, is summarized. Then, this formulation is utilized to develop a new four-node quadrilateral inverse-shell element, iQS4, which further extends the practical utility of iFEM for shape sensing of large-scale structures including marine structures. Various numerical examples are presented and it is demonstrated that the iQS4 formulation is robust with respect to the membrane- and shear-locking phenomena. Moreover, the iFEM/iQS4 methodology is applied to various types of marine structures including a stiffened plate, a chemical tanker, and a container ship. To simulate experimentally measured strains and to establish reference displacements, a coupled hydrodynamic and high-fidelity finite element analyses are performed. Utilizing the simulated strain-sensor strains, iFEM analysis of each marine structure is performed. As a result, the optimum locations of the on-board strain sensors are determined for each marine structure.;Furthermore, a novel isogeometric Kirchhoff-Love inverse-shell element (iKLS) for more accurate shape-sensing analysis of curved/complex shell structures is presented. The new formulation employs the iFEM as a general framework and the non-uniform rational B-splines (NURBS) as the discretization technology for both structural geometry and displacement domain. Therefore, this new formulation couples the concept of isogeometric analysis with iFEM methodology and creates an innovative "isogeometric iFEM formulation". The superior shape-sensing capability of the isogeometric iFEM formulation (i.e., iKLS) is demonstrated for curved shell structures when using low-fidelity discretizations with few strain sensors. Finally, an improved iFEM formulation for dealing with shape and stress sensing of multilayered composite and sandwich plate/shell structures is described. The present iFEM formulation is based upon the minimization of a weighted-least-squares functional that uses the complete set of strain measures of refined zigzag theory (RZT). A new three-node inverse-shell element, i3-RZT, is developed based on the enhanced iFEM formulation. Various validation and demonstration problems are solved to examine the precision of the iFEM/i3-RZT methodology. The numerical results demonstrate the superior accuracy and robustness of the i3-RZT element for performing accurate shape and stress sensing of complex composite structures. In conclusion, all proposed iFEM frameworks are computationally efficient, accurate, and powerful, hence they can be helpful for shape sensing and SHM of general engineering structures, especially of marine structures
Force and temperature sensors based on organic thin-film transistor and ferroelectric co-polymer
Get PDFThis thesis presents the development of tactile force and temperature sensors formed by coupling an organic thin-film transistor with a ferroelectric polymer-based parallel-plate capacitor. Ferroelectric material polyvinylidene fluoride trifluoroethylene (P(VDF-TrFE)) sandwiched between two metal electrodes in a parallel plate capacitor structure was coupled to the gate electrode of a low-voltage organic thin-film transistor (OTFT) for signal amplification and voltage readout. To ensure low-voltage operation of the sensing circuit, low-voltage transistor operation was necessary. This was enabled through use of an ultra-thin bi-layer gate dielectric comprised of aluminium oxide (AlOx), formed by the UV/ozone oxidation of aluminium, and a self-assembled monolayer (SAM) of phosphonic acid produced by vacuum deposition. The OTFT was optimised with respect to its dielectric and semiconductor; whereby the length of the SAM's alkyl chain and semiconductor deposition conditions on OTFT electrical and structural properties were studied. An air-stable organic semiconductor dinaphtho[2,3-b:2',3'-f]thieno[3,2-b]thiophene (DNTT) was implemented to create OTFTs with improved mobility and electrical stability. Furthermore, two commercially available polyethylene naphthalate (PEN) plastic foils were compared for use as flexible substrates for OTFTs. Response of the P(VDF-TrFE)/OTFT sensor to force and temperature was investigated and results show that the sensor has a linear response to applied constant temperature whereas it responds logarithmically to static compressive force, regardless of whether P(VDF-TrFE) is in the ferroelectric or paraelectric state.This thesis presents the development of tactile force and temperature sensors formed by coupling an organic thin-film transistor with a ferroelectric polymer-based parallel-plate capacitor. Ferroelectric material polyvinylidene fluoride trifluoroethylene (P(VDF-TrFE)) sandwiched between two metal electrodes in a parallel plate capacitor structure was coupled to the gate electrode of a low-voltage organic thin-film transistor (OTFT) for signal amplification and voltage readout. To ensure low-voltage operation of the sensing circuit, low-voltage transistor operation was necessary. This was enabled through use of an ultra-thin bi-layer gate dielectric comprised of aluminium oxide (AlOx), formed by the UV/ozone oxidation of aluminium, and a self-assembled monolayer (SAM) of phosphonic acid produced by vacuum deposition. The OTFT was optimised with respect to its dielectric and semiconductor; whereby the length of the SAM's alkyl chain and semiconductor deposition conditions on OTFT electrical and structural properties were studied. An air-stable organic semiconductor dinaphtho[2,3-b:2',3'-f]thieno[3,2-b]thiophene (DNTT) was implemented to create OTFTs with improved mobility and electrical stability. Furthermore, two commercially available polyethylene naphthalate (PEN) plastic foils were compared for use as flexible substrates for OTFTs. Response of the P(VDF-TrFE)/OTFT sensor to force and temperature was investigated and results show that the sensor has a linear response to applied constant temperature whereas it responds logarithmically to static compressive force, regardless of whether P(VDF-TrFE) is in the ferroelectric or paraelectric state
Shawkirk
No full textThis Masters Thesis contains both the original short-story cycle Shawkirk and a critical analysis of the work. Shawkirk encompasses eight short stories linked by characters and setting, with a different narrator for each story. The focus is mainly on the disaffected youth in the titular suburb, although the first and last stories deviate from this formula, in setting and character respectively. The cycle covers roughly half a year - beginning with a summer scout camp and ending around the Christmas period. Throughout the year, several plotlines develop - most importantly the various attempts by the younger characters to escape Shawkirk's poisonous influence.In the critical analysis I examine several short story collections by established authors, and how their work influenced the structure and style of my own collection. With focus on developing setting, I refer back to Shawkirk and how it compares with other short-story cycles, while discussing how multiple narrators can influence this development.This Masters Thesis contains both the original short-story cycle Shawkirk and a critical analysis of the work. Shawkirk encompasses eight short stories linked by characters and setting, with a different narrator for each story. The focus is mainly on the disaffected youth in the titular suburb, although the first and last stories deviate from this formula, in setting and character respectively. The cycle covers roughly half a year - beginning with a summer scout camp and ending around the Christmas period. Throughout the year, several plotlines develop - most importantly the various attempts by the younger characters to escape Shawkirk's poisonous influence.In the critical analysis I examine several short story collections by established authors, and how their work influenced the structure and style of my own collection. With focus on developing setting, I refer back to Shawkirk and how it compares with other short-story cycles, while discussing how multiple narrators can influence this development
A multi-disciplinary study of the early stages of beta amyloid aggregation
Get PDFAmyloid fibrils have been linked to many diseases, with different proteins being associated with different health issues. The aggregation of Beta Amyloid (Aß) peptides can lead to Alzheimer's disease. These peptides are found in the body naturally, although Aß function is still not clear. The aggregation process is still a matter of research, however it is widely accepted that a lag period is followed by rapid aggregate growth and then a saturation phase where growth halts. Understanding how and why this happens is imperative for disease prevention. It has been found that toxicity occurs during the formation of oligomer. Collaborative work involving simulation and experimental methods has become commonplace, improving the understanding of this process. Consequently, the work presented here is a multidisciplinary study of the early stages of amyloid aggregation in Aß1-40 and Aß1-42. These are the two most common species and are 40 and 42 amino acid groups long respectively. They have been studied through the use of Molecular Dynamics (MD) and Monte Carlo (MC) simulations, which have been complemented by probing Aß1-40 with the experimental methods: fluorescence spectroscopy, fluorescence anisotropy and dynamic light scattering.Experimentation proved challenging, due to the noise encountered in Aß samples and alternative solvent compositions were studied in an attempt to overcome this. These experiments had limited success but when combined with simulation models, revealed potential insight into the aggregation through the movements of the tyrosine (Tyr) side-chain, an amino acid group found in the Aß proteins. MD simulations and MC simulations were used in order to probe the underlying mechanisms surrounding Tyr movements and their environments during the aggregation process and how it affects fluorescence anisotropy. The MD simulations also revealed conformational changes in the protein due to the presence of ions and discovered two new Tyr orientations which occur in protofibrils.Amyloid fibrils have been linked to many diseases, with different proteins being associated with different health issues. The aggregation of Beta Amyloid (Aß) peptides can lead to Alzheimer's disease. These peptides are found in the body naturally, although Aß function is still not clear. The aggregation process is still a matter of research, however it is widely accepted that a lag period is followed by rapid aggregate growth and then a saturation phase where growth halts. Understanding how and why this happens is imperative for disease prevention. It has been found that toxicity occurs during the formation of oligomer. Collaborative work involving simulation and experimental methods has become commonplace, improving the understanding of this process. Consequently, the work presented here is a multidisciplinary study of the early stages of amyloid aggregation in Aß1-40 and Aß1-42. These are the two most common species and are 40 and 42 amino acid groups long respectively. They have been studied through the use of Molecular Dynamics (MD) and Monte Carlo (MC) simulations, which have been complemented by probing Aß1-40 with the experimental methods: fluorescence spectroscopy, fluorescence anisotropy and dynamic light scattering.Experimentation proved challenging, due to the noise encountered in Aß samples and alternative solvent compositions were studied in an attempt to overcome this. These experiments had limited success but when combined with simulation models, revealed potential insight into the aggregation through the movements of the tyrosine (Tyr) side-chain, an amino acid group found in the Aß proteins. MD simulations and MC simulations were used in order to probe the underlying mechanisms surrounding Tyr movements and their environments during the aggregation process and how it affects fluorescence anisotropy. The MD simulations also revealed conformational changes in the protein due to the presence of ions and discovered two new Tyr orientations which occur in protofibrils
Air source heat pump modelling for dynamic building simulation tools based on standard test data
Get PDFAir source heat pumps (ASHP) are increasingly of interest in the UK and Europe, due to national commitments around emissions reductions and the greater use of renewables. This raises issues around the optimisation of installation design approaches, and the potential for ASHP to contribute to demand flexibility. Dynamic modelling is a useful tool for addressing such issues. It is also beginning to play a role in performance estimation under National Calculation Methodologies. There is currently no broadly accepted method for the creation of models of air-to-water heat pump performance for dynamic building simulation tools based on standard testing processes. Such a method is proposed. An analysis of ASHP theory and behaviour is undertaken, and used to inform a review of modelling methods in the literature. The "greybox" approach is selected, and adapted to work with data of the type output by European Standard EN 14511 for the performance testing of heat pumps. The wide applicability of the proposed modelling method is demonstrated through application to EN 14511 data for 45 ASHP units. Three of the models developed are implemented in building energy simulation tool ESP-r. Simulations results are within the range found in field trials, and are comparable to the predictions of other modelling methods. The method can differentiate between higher and lower quality ASHP, and predictions follow expected trends when the parameters of the modelled heating system are changed. It is concluded that the method is valid for simulations focussing on the integrated performance of building and heating systems. The main limitation found is that humidity can have a significant impact on performance, and EN 14511 performance data does not allow sensitivity to humidity to be assessed. Recommendations are made for extensions to standard testing processes to aid the production of dynamic models.Air source heat pumps (ASHP) are increasingly of interest in the UK and Europe, due to national commitments around emissions reductions and the greater use of renewables. This raises issues around the optimisation of installation design approaches, and the potential for ASHP to contribute to demand flexibility. Dynamic modelling is a useful tool for addressing such issues. It is also beginning to play a role in performance estimation under National Calculation Methodologies. There is currently no broadly accepted method for the creation of models of air-to-water heat pump performance for dynamic building simulation tools based on standard testing processes. Such a method is proposed. An analysis of ASHP theory and behaviour is undertaken, and used to inform a review of modelling methods in the literature. The "greybox" approach is selected, and adapted to work with data of the type output by European Standard EN 14511 for the performance testing of heat pumps. The wide applicability of the proposed modelling method is demonstrated through application to EN 14511 data for 45 ASHP units. Three of the models developed are implemented in building energy simulation tool ESP-r. Simulations results are within the range found in field trials, and are comparable to the predictions of other modelling methods. The method can differentiate between higher and lower quality ASHP, and predictions follow expected trends when the parameters of the modelled heating system are changed. It is concluded that the method is valid for simulations focussing on the integrated performance of building and heating systems. The main limitation found is that humidity can have a significant impact on performance, and EN 14511 performance data does not allow sensitivity to humidity to be assessed. Recommendations are made for extensions to standard testing processes to aid the production of dynamic models
Stereo vision-based object detection algorithm for USV using faster R-CNN
Get PDFThe missions at sea require automation due to human accessibility and labour constraints. Accordingly, the requirement for a USV is highlighted for surveillance, environment investigation, and so on. The fully automated USV requires the reliable detection system in accordance with the prerequisite to safe collision avoidance. For this, USVs are equipped with a number of equipment, but these units are expensive and demand extra loading capacity. Therefore, it is necessary to simplify such equipment, and at the same time, essential data for safe collision avoidance should be acquired without loss.;The equipment simplification potentially can be achieved by using a vision sensor. The vision sensor that has been used in the conventional USV only tracks the marine object. For safe collision avoidance, the type of object detected and the distance to the object are also required. This additional information requires direct observation from human or other equipment support. If the vision sensor can be used to estimate the distance and the object type, the equipment for USV can be simplified.;The purpose of this research is the development of vision-based object detection algorithm that recognises a marine object and estimates the position and distance to the object for USV. Faster R-CNN, a state-of-the-art image processing technique that imitates human visual perception, is used to recognise and localise object on a captured frame from a vision sensor. In order to obtain the distance to the recognised object, stereo vision based depth estimation technique is used.;Therefore, a stereo camera was used in this research. By combining these two techniques, real-time marine object detection algorithm was implemented and the performance of this algorithm is verified by model ship detection test in towing tank. The test results showed that this algorithm is potentially applicable to real USV.The missions at sea require automation due to human accessibility and labour constraints. Accordingly, the requirement for a USV is highlighted for surveillance, environment investigation, and so on. The fully automated USV requires the reliable detection system in accordance with the prerequisite to safe collision avoidance. For this, USVs are equipped with a number of equipment, but these units are expensive and demand extra loading capacity. Therefore, it is necessary to simplify such equipment, and at the same time, essential data for safe collision avoidance should be acquired without loss.;The equipment simplification potentially can be achieved by using a vision sensor. The vision sensor that has been used in the conventional USV only tracks the marine object. For safe collision avoidance, the type of object detected and the distance to the object are also required. This additional information requires direct observation from human or other equipment support. If the vision sensor can be used to estimate the distance and the object type, the equipment for USV can be simplified.;The purpose of this research is the development of vision-based object detection algorithm that recognises a marine object and estimates the position and distance to the object for USV. Faster R-CNN, a state-of-the-art image processing technique that imitates human visual perception, is used to recognise and localise object on a captured frame from a vision sensor. In order to obtain the distance to the recognised object, stereo vision based depth estimation technique is used.;Therefore, a stereo camera was used in this research. By combining these two techniques, real-time marine object detection algorithm was implemented and the performance of this algorithm is verified by model ship detection test in towing tank. The test results showed that this algorithm is potentially applicable to real USV
Integration of large wind farms to weak power grids
Get PDFPower grids are changing significantly with the introduction of large amounts of renewable energy (especially wind) into the system. Integration of wind energy into the grid is challenging as, firstly it increases penetration stresses when compared to conventional generation as the wind is intermittent and fluctuates in power output. Secondly, most of the wind farms are located in offshore or rural areas which have good wind conditions. The grid in these regions is not normally strong. Most of the modern variable speed wind turbines use voltage source converters (VSCs) for grid integration. However, integrating VSCs to weak power grids will cause instability when a large amount of active power is transferred to the grid. In this thesis, the integration of wind farms to very weak power grids is investigated. A multiple input, multiple output (MIMO) model of the grid side VSC of a wind turbine is developed in the frequency domain in which the d-axis of the synchronous reference frame (SRF) is aligned with the grid voltage. Then, this model has been used as the basis for modelling the multiple parallel converters in the frequency domain. In this thesis, to improve the stability of the very weak grid connected of VSCs, a control method based on the d- and q- axis current error is introduced. This controller compensates the output angle of the phase locked loop (PLL) and the voltage amplitude of the converter. Using this controller, full rated active power transfer and fault ride-through are achieved under very weak grid connection. Furthermore, a stabiliser controller based on virtual impedance is proposed in this thesis to achieve stable operation of a very weak grid connected VSC. This stabilising control method enables the VSC to operate at full power and to ride-through faults under very weak grid conditions. Based on this principle, an external device is proposed that can be utilised and connected to a weak point of the grid to allow a large amount of VSC interfaced power generation (e.g. wind power) to be connected to the grid without introducing stability issues.Power grids are changing significantly with the introduction of large amounts of renewable energy (especially wind) into the system. Integration of wind energy into the grid is challenging as, firstly it increases penetration stresses when compared to conventional generation as the wind is intermittent and fluctuates in power output. Secondly, most of the wind farms are located in offshore or rural areas which have good wind conditions. The grid in these regions is not normally strong. Most of the modern variable speed wind turbines use voltage source converters (VSCs) for grid integration. However, integrating VSCs to weak power grids will cause instability when a large amount of active power is transferred to the grid. In this thesis, the integration of wind farms to very weak power grids is investigated. A multiple input, multiple output (MIMO) model of the grid side VSC of a wind turbine is developed in the frequency domain in which the d-axis of the synchronous reference frame (SRF) is aligned with the grid voltage. Then, this model has been used as the basis for modelling the multiple parallel converters in the frequency domain. In this thesis, to improve the stability of the very weak grid connected of VSCs, a control method based on the d- and q- axis current error is introduced. This controller compensates the output angle of the phase locked loop (PLL) and the voltage amplitude of the converter. Using this controller, full rated active power transfer and fault ride-through are achieved under very weak grid connection. Furthermore, a stabiliser controller based on virtual impedance is proposed in this thesis to achieve stable operation of a very weak grid connected VSC. This stabilising control method enables the VSC to operate at full power and to ride-through faults under very weak grid conditions. Based on this principle, an external device is proposed that can be utilised and connected to a weak point of the grid to allow a large amount of VSC interfaced power generation (e.g. wind power) to be connected to the grid without introducing stability issues
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