95 research outputs found
Correction: MBFair: a model-based verification methodology for detecting violations of individual fairness
No full text137Correction to: Software and Systems Modelinghttps://doi.org/10.1007/s10270-024-01184-y. The article "MBFair: a model-based verification methodology for detecting violations of individual fairness", written by Qusai Ramadan, Marco Konersmann, Amir Shayan Ahmadian, Jan Jürjens and Steffen Staab was originally published electronically on the publisher’s internet portal on 10 June 2024 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 31 December 2024 to © The Author(s) 2024 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.24
Exergoeconomic and multi-objective optimization of a solar thermochemical hydrogen production plant with heat recovery
No full textA solar hydrogen production plant based on a four-step copper-chlorine (Cu-Cl) thermochemical cycle is presented and analyzed in this paper. The integrated system includes a pressurized solar power tower, gas turbine unit, phase change material (PCM) for thermal energy storage (TES), Cu-Cl cycle, regenerative steam Rankine cycle (SRC), and a heat recovery unit. A predictive model is developed for energy, exergy, and exergo-economic analyses of the proposed system. A parametric study is also conducted to investigate the effect of major parameters on the system performance. The system is optimized with a non-dominated sorting genetic algorithm-II (NSGA-II) considering exergy efficiency and product cost per unit exergy as the two objective functions. The results indicate that the energy and exergy efficiencies of the overall system are 48.2% and 45%, respectively, while the total product cost per unit of exergy is found to be 11.94/GJ, respectively
Representation theory of SU(2) and SU(3) with applications to spin and quark models
No full textIn this thesis we provide an elementary introduction in finite dimensional representation theory of the Lie groups SU(2) and SU(3) for undergraduate students in physics and mathematics. We will also give two application of representation theory of these two groups in physics: the spin and quark models. We begin with first discussing representation theory for finite groups to create intuition for representations. We will explain notions such as intertwining maps and complete reducibility and we will mention some application of representation theory of finite groups inquantum mechanics. Hereafter, we begin with representation theory for Lie groups and Lie algebras, especially the groups SO(3) and SU(2), as these groups will play an important role in the description of spin. One of the main results is that SU(2) is the universal cover of SO(3). Furthermore, we give a description of spin by means of representation theory of SO(3) and its Lie algebra so(3). We will show that half integer representations of the Lie algebra so(3) cannot be exponentiated to representations of the Lie group SO(3), but it can be exponentiated to its universal cover SU(2). Moreover, we study the irreducible representations of SO(3) inside the Hilbert space L2(R3). We will argue that one of the simplest quantum Hilbert spaces of a particle L2(R3), can be modified to the completion of the tensor product L2(R3) ⊗V, where, V is a finite dimensional Hilbert space that incorporates the internal degrees of freedom: spin. V carries an irreducible projective representation of SO(3). We will also discuss the addition of angular momentum of two particles in quantum mechanics. For this, we show how the tensor product of irreducible representations V and W of so(3) decomposes into SO(3) invariant subspaces of L2(R3). Hereafter, we will turn to representation theory of the Lie group SU(3) for setting up the mathematical framework for analysing the quark model. We will proof that there is a one-to-one correspondence between the irreducible representations of sl(3;C)and SU(3). We will also proof the theorem of the highest weight by which we can classify all the irreducible representations of SU(3) and sl(3;C) by their highest weight. We will also introduce the notion of the Weyl group and show that the Weyl group is a symmetry of weights of the finite dimensional representation of sl(3;C). Other properties of these representation, such as the dimension of the irreducible representations of sl(3;C) will be provided. Lastly, the quark model is discussed by means of representation theory of SU(3). We will show how this model can be used to classify two type of particles which also interact by means of the strong force: baryons and mesons. We show that we can classify the lightest mesons and baryons in so-called multiplets by the irreducible representations of SU(3). However, we will also introduce a modification of the strong force which further refines this model. A topic for further study would be how the symmetry group SU(3) describing Quantum Chromo Dynamics (QCD) can be used for the description of mesons and baryons.Applied Mathematics | Applied Physic
Analysis of Offshore Protective Berms using FEM and MPM
No full textBy increase in knowledge and complexity of the projects, worldwide, more attention towards safety provision in projects is being paid. With growth in waterway traffic the need of safety provision for structures crossing navigable waters increases. Especially bridge piers and immersed tunnels on the see floor or at tunnel approaches are at bigger risk of being hit by ships which have lost their navigational course due to any reasons. Therefore availability of collision protective systems is essential. A number of different methods are being used worldwide as protective systems while for the full frontal collision, protective berms are the most convenient systems. This research investigates the possibility of calculations for these berms using numerical modelling tools such as Finite Element Method (FEM) and Material Point Method (MPM). FEM is a well-known and proven tool in engineering world while MPM is a newly developed tool that is considered as an update of FEM. In MPM the material state and stresses are stored in material points that can freely move though the mesh. This tool is highly useful for problems with high expected deformations or dynamic calculations where FEM is not considered as an ideal tool and could fail. Furthermore, also, a simplified analytical method has been presented in this report.At present MPM is being developed around the world. Plaxis, which is a well-known software developer especially for Geo-Engineering applications, is currently developing software that provides MPM modelling. For this research, the Plaxis 2D software has been used for MPM under confidentiality terms. As mentioned, the software is in its development stage therefore some issues where expected. The FEM models are also created using the internationally used Plaxis 2D FEM version. The reliability of the MPM and also FEM models in dynamic calculations was analyzed in this research allowing for a better understanding for the final model which represents the ship-berm collision problem. Two models (static and dynamic) were created in both FEM and MPM which then verified and compared. Therefore it was concluded that MPM can be considered as a reliable tool for dynamic calculations since the obtained results were similar or comparable with FEM and analytical solutions. The final models in both FEM and MPM however, did not provide the required results that could help to understand the ship-berm collision mechanism and/or the stress situations within the soil (only partial results were obtained). The FEM model showed very unrealistic and inaccurate results. The constant predefined contact area between the ship and berm is considered to be the main issue in this model; on the other hand, due to encountered issues with MPM, the MPM simulation could not be fully performed in terms of minimum required time steps. Nevertheless the partial simulations with a limited simulation time, were found to be realistic and in accordance with expectation, suggesting the capability of MPM for dynamic calculation after the necessary developments. As conclusion, this report does not recommend the usage of FEM for such a modelling and considers MPM a good possible tool to be used after the necessary developments in the near future. Meanwhile the presented simplified analytical method could provide a rough estimation for required berm length. In addition a FEM model has also been suggested in this report allowing for the user to have an insight on the stress propagation within the soil.Geo-Engineerin
Application of Continuous Reinforcement Learning on Innovative Control Effector Aircraft: Online Actor-Critic-Based Adaptive Control for a Tailless Aircraft with Innovative Control Effectors
No full textHigher levels of autonomy in aerospace systems is an urgent requirement, considering the increase in control task difficulties, and the need for adaptability of the complex systems. Reinforcement learning (RL) control is one of the promising approaches for adaptive control of air vehicles that are designed for automation. Conventional discrete reinforcement learning methods fail in providing satisfactory performance for flight control systems (FCSs), especially for a complex configuration of a tailless over-actuated aircraft. The lack of efficiency of the discrete controller in exploration for finding the optimal policy, the so-called problem of 'curse of dimensionality', results in an approach that is not suitable for online implementation. Also, the achieved discrete non-smooth control policy usually does not apply to the real world control surfaces. This paper studies the experiments with Heuristic Dynamic Programming (HDP), a method obtained from adaptive critic design (ACDs), as a continuous reinforcement learning approach. ACD methods can capture the nonlinearities in the complex dynamics of the aircraft while solving the control problem computationally efficient by using continuous states and action spaces. Such qualities make ACDs suitable for online FCS design for unstable systems like tailless aircraft. In this paper, the ACD-based controller is developed and implemented for the Innovative Control Effector (ICE) aircraft, a highly maneuverable aircraft with redundancy in its control effectors suite. The coupled control effectors configuration has strong interactions and, therefore, proposes a need for proper control allocation. The online simulation results show the accuracy of the designed continuous RL controller in the longitudinal control of the aircraft using different sets of control effectors. The proposed approach also shows significant improvements in the tracking performance and control policy smoothness (e.g., compared to discrete methods).Aerospace Engineerin
Replacing the acquisition function in Bayesian optimization by a neural network: How effectively do meta-learned acquisition functions in Bayesian optimization perform when optimizing for control variates of unknown functions, as compared to BO with standard acquisition functions
No full textBayesian Optimization (BO) has demonstrated significant utility across numerous applications. However, due to it being designed as a universal optimizer, its performance can often be suboptimal in specialized environments. To overcome this issue, research has been conducted into the application of transfer learning for enhancing BO performance in these specialized contexts. This paper describes the research done into evaluating the MetaBO algorithm in some specific environments. MetaBO innovates by substituting the acquisition function component in BO with a neural network that serves as an acquisition function, trained via a reinforcement learning framework. Although the results indicate that the algorithm's performance is not optimal in the environments tested, these limitations are ascribed to elements of the implementation rather than the concept of the algorithm itself. Consequently, further research is necessary to refine the implementation process and fully exploit the potential of the MetaBO algorithm.CSE3000 Research ProjectComputer Science and Engineerin
Online Actor-Critic-Based Adaptive Control for a Tailless Aircraft with Innovative Control Effectors
No full textConventional discrete reinforcement learning methods fail in providing satisfactory performance for online Flight Control Systems (FCSs). The lack of efficiency of the discrete controller in exploration for finding the optimal policy, the so-called problem of ’curse of dimensionality’, results in an approach that is not suitable for online implementation. the Innovative Control Effector (ICE) aircraft is a highly maneuverable tailless aircraft with redundancy in its control effectors suite. This paper studies the experiments with adaptive critic design (ACDs) for longitudinal control of ICE aircraft. The online simulation results show the accuracy of the designed continuous RL controller in the attitude and altitude control of the aircraft using different sets of control effectors. The proposed approach also shows significant improvements in the tracking performance and control policy smoothness (e.g., compared to discrete methods).Virtual/online event due to COVID-19Control & Simulatio
An interactive assessment framework for residential space layouts using pix2pix predictive model at the early-stage building design
No full textPurpose: In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design. Design/methodology/approach: A methodology using an image-based deep learning model called pix2pix is proposed to predict the overall daylight, energy and ventilation performance of a given residential building space layout. The proposed methodology is then evaluated by being applied to 300 sample apartment units in Tehran, Iran. Four pix2pix models were trained to predict illuminance, spatial daylight autonomy (sDA), primary energy intensity and ventilation maps. The simulation results were considered ground truth. Findings: The results showed an average structural similarity index measure (SSIM) of 0.86 and 0.81 for the predicted illuminance and sDA maps, respectively, and an average score of 88% for the predicted primary energy intensity and ventilation representative maps, each of which is outputted within three seconds. Originality/value: The proposed framework in this study helps upskilling the design professionals involved with the architecture, engineering and construction (AEC) industry through engaging artificial intelligence in human–computer interactions. The specific novelties of this research are: first, evaluating indoor environmental metrics (daylight and ventilation) alongside the energy performance of space layouts using pix2pix model, second, widening the assessment scope to a group of spaces forming an apartment layout at five different floors and third, incorporating the impact of building context on the intended objectives.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.History, Form & Aesthetic
A novel machine learning-based framework for mapping outdoor thermal comfort
No full textRapid urbanization and global warming have increased heat stress in urban areas. This in turn makes using indoor space more compelling and leads to more energy consumption. Therefore, paying attention to outdoor spaces design with thermal comfort in mind becomes more important since outdoor spaces can host a variety of activities. This research aims to introduce a machine learning-based framework to predict the effects of different urban configurations (i.e. different greening configurations and types, different façade materials, and different urban geometry) on outdoor thermal comfort through training a pix2pix Convolutional generative adversarial network (cGAN) model. For the training of the machine learning model, a dataset consisting of 208 coupled pictures of input and output has been created. The simulation of this data has been carried out by ENVI-met. The resulting machine learning model had a Structural Similarity Index (SSIM) of 96% on the test dataset with the highest SSIM of 97.08 and lowest of 94.43 which shows the high accuracy of the model and it could have reached an answer in 3 s compared to the 30-min average time for ENVI-met simulation. The resulting model shows great promise for assisting researchers and urban designers in studying existing urban contexts or planning new developments. HIGHLIGHTS Machine learning use in outdoor thermal comfort assessment has been investigated. Vegetation, urban geometry, surface albedo, and water bodies have been studied parameters. Vegetation and street orientation have the highest and water bodies have the least impact on outdoor thermal comfort. Pix2pix algorithm implementation could create thermal comfort maps with 96% SSIM.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.History, Form & Aesthetic
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