157082 research outputs found
Sort by
A Stochastic Model of Mutual Insurance under Heterogeneous Time Preferences
No full textThis research examines the premium control problem of a mutual insurance company when its policyholders have heterogeneous (or present-biased) time preferences. When decisions are made collectively by policyholders with diverse time preferences, utilitarian aggregation results in time-inconsistent time preferences. To address time inconsistency, we employ an intrapersonal game-theoretic framework and seek a time-consistent equilibrium strategy. The equilibrium strategy recommends collecting premiums at the minimal rate when the mutual insurer’s reserve surpasses a specified threshold and at the maximal rate when it falls below this threshold. We find that higher heterogeneity (or equivalently, the decreasing impatience) of policyholders’ time preferences will lead to lower reserve thresholds. Our model offers insights for mutual insurers to design premium policies when their policyholders have diverse time preferences
Integrating External Tools with Large Language Models (LLMs) to Improve Accuracy
No full textThis paper deals with improving querying large language models (LLMs). It is well-known that without relevant contextual information, LLMs can provide poor-quality responses or tend to hallucinate. Several initiatives have proposed integrating LLMs with external tools to provide them with up-to-date data to improve accuracy. In this paper, we propose a framework to integrate external tools to enhance the capabilities of LLMs in answering queries in educational settings. Precisely, we develop a framework that allows accessing external APIs to request additional relevant information. Integrated tools can also provide computational capabilities such as calculators or calendars. The proposed framework has been evaluated using datasets from the Multi-Modal Language Understanding (MMLU) collection. The data consists of questions on mathematical and scientific reasoning. Results compared to basic OpenAI model show that the proposed approach significantly improves performance. On mathematical questions, our framework scores 83% where basic OpenAI scores 36%. In scientific reasoning, the difference is even more significant with 88% for the proposed method as compared to 56% for the basic OpenAI model. These promising results open the way to creating complex computing ecosystems around LLMs to make their use more natural to support various tasks and activities.</p
Fault interruption scheme for HVDC systems using GaN-HEMT and VCB
No full textPower electronics switching devices played an important role in high-voltage DC circuit breaker development. Timely isolation of faulty portions of an HVDC transmission line from a healthy system is a basic requirement for a fault interruption. In this scenario, the integration of hybrid DC circuit breakers (HDCCBs) with wideband-gap semiconductor devices enables the effective management of high power, currents, and voltages. The SiC-MESFET and the GaN-HEMT are commonly used wideband-gap-based semiconductor devices. This paper introduces a fault interruption scheme for HVDC power systems, featuring the advancement of a hybrid DC circuit breaker. The proposed HDCCB design consists of two parts, one part is based on a VCB as a mechanical circuit breaker, and the second part involves electronic switches for fault interruption. The electronic switches are designed through the combination of GaN and HEMT to achieve fast switching to achieve rapid interruption of fault current. The system model is implemented through a Simulink model to perform a comparative analysis between the presented and existing protection topologies. Current commutation is achieved through the attainment of artificial zero current crossing to interrupt the DC fault. GaN-HEMT emerges as a more reliable and fast switching element compared to other electronic switches like Sic-MESFET as validated by the presented simulative results. The presented model shows better fault-clearing times of 2.2 ms and 2 ms for experimental parameters of (500 kV and 9kA) and (100 kV and 10kA), respectively. This fault-clearing time shows an improvement of 52.38% and 50% compared to the SiC-MESFET-based electronic switches used by the existing mechanisms. The outcomes of the proposed design are evaluated in terms of fault current, commutated current, and voltage across the commutated capacitor.</p
Water content in pure CO<sub>2</sub> and CO<sub>2</sub>-rich mixtures using the DSH analytical technique
No full textThe accurate determination of water content in equilibrium with hydrates helps to prevent operational problems related to flow assurance, and it is essential for the emerging Carbon Capture and Storage (CCS) processes for decarbonization. However, the experimental challenges associated with these measurements cause a scarcity of data. The development of the Differential Scanning Hygrometer (DSH) method has increased the number of water content reports for CO2-rich systems in equilibrium with hydrates. It monitors not absolute values but fluctuations in the water content due to the formation of ice or dew inside a temperature-controlled tube. Here, we provide experimental and modeling investigation for water content on pure CO2 and two CO2-rich mixtures (CO2+CH4 and CO2+CH4+N2) in equilibrium with hydrates: the sCPA and the SRK+EMS equations of state were used to model the obtained experimental data, both using the van der Waals-Platteeuw (vdW-P) model for the hydrate phase
Evaluating the role of cap rock in controlling natural accumulation and storage of carbon dioxide in the East Irish Sea Basin, UK
No full textNaturally occurring CO2 in some gas fields in the East Irish Sea Basin are proof of the concept of effective containment there since Paleogene emplacement. A large well and geophysical database affords the opportunity to examine the geological controls responsible for the CO2 accumulations. Halite-dominated members, such as the Fylde Halite, within the Mercia Mudstone Group cap rock are thickest in the Keys Basin, a sub-basin where natural CO2 resides, but are also present elsewhere before becoming absent southwards, where mudstone-dominated members proportionally increase and contain laterally continuous sandstone interbeds. The lack of petroleum shows above the evaporite-rich units and their consistent presence within underlying argillaceous sections highlights the significance of the halite-dominated members as effective cap rocks. Multiple regional pressure trends indicate that the aquifer of the Keys Basin is relatively underpressured and isolated from the wider aquifer by bounding faults and graben. The combination of aquifer isolation, igneous intrusions and the overlying Fylde Halite Member is considered responsible for the local preservation of natural CO2. While the thick, halite-dominated cap rock will reduce the risk to containment for storage prospects in the Keys Basin, the isolation of the aquifer may cause rapid pressurization from CO2 injection that limits technically achievable capacities
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection
No full textPrevious research on behaviour-based attack detection for networks of IoT devices has resulted in machine learning models whose ability to adapt to unseen data is limited and often not demonstrated. This paper presents IoTGeM, an approach for modelling IoT network attacks that focuses on generalizability, yet also leads to better detection and performance. We first introduce an improved rolling window approach for feature extraction. To reduce overfitting, we then apply a multi-step feature selection process where a Genetic Algorithm (GA) is uniquely guided by exogenous feedback from a separate, independent dataset. To prevent common data leaks that have limited previous models, we build and test our models using strictly isolated train and test datasets. The resulting models are rigorously evaluated using a diverse portfolio of machine learning algorithms and datasets. Our window-based models demonstrate superior generalization compared to traditional flow-based models, particularly when tested on unseen datasets. On these stringent, cross-dataset tests, IoTGeM achieves F1 scores of 99% for ACK, HTTP, SYN, MHD, and PS attacks, as well as a 94% F1 score for UDP attacks. Finally, we build confidence in the models by using the SHAP (SHapley Additive exPlanations) explainable AI technique, allowing us to identify the specific features that underlie the accurate detection of attacks.</p
Effects of semi-rigid behavior on the seismic performance of the precast shear wall with a box-shaped connection joint
No full textBolted connections with obvious semi-rigid characteristics will experience additional moments caused by the second-order effects in structures, leading to inferior seismic performance of precast shear walls compared to cast-in-place shear walls. In order to investigate the influence of semi-rigidity, a new box-shaped connection with apparent semi-rigid features has been proposed. Cyclic loading tests were conducted on a full-scale shear wall specimen (BPSW) with a box-shaped connection and a cast-in-place shear wall specimen (SW1). Failure characteristics, seismic performance, and deformation composition were comprehensively analyzed. Test results indicate that that both BPSW and SW1 exhibit the same bending failure mode. The seismic performance, as indicated by the hysteretic envelope area in BPSW, is slightly smaller than that of SW1. The reduced ductility, initial stiffness, and energy dissipation in BPSW can be attributed to the semi-rigid behavior, which affects the deformation behavior of the precast shear wall structure. Additionally, the deformation composition analysis reveals that rotational deformation of the new box-shaped connection in BPSW cannot be ignored as it accounts for more than 30% of the horizontal displacement. In accordance with previous models, a theoretical model for rotational deformation that offers insights into the semi-rigid nature and seismic performance of the box-shaped connection is proposed. The proposed model demonstrates good agreement with experimental results and provides valuable insights into the semi-rigid behavior and seismic response of such precast connections.</p
Categorising residential energy demand datasets in the UK
No full textAccess to high-quality residential energy demand data is crucial for research and policymaking. In the transition to a modern, digitalised energy system, datasets should be visible and accessible to end users. However, the absence of standardised data release guidelines and metadata standards creates challenges in data visibility, accessibility, and comparability. These challenges lead to repetitive and time-consuming searches for relevant datasets. This study examines twenty-four UK residential energy demand datasets, highlighting inconsistencies in how they are catalogued, documented, and structured. A novel classification scheme is introduced to systematically document dataset attributes, scope, and contextual variables. Subsequent categorisation of the twenty-four datasets using the classification scheme enhances data discovery, comparability, and consistency, while also identifying gaps. This article also addresses the evolving landscape of residential energy demand datasets and policy and the role of data in supporting efforts to decarbonise the building stock. This work highlights the need for greater standardisation and accessibility, emphasising the importance of harmonised metadata, improved documentation, and cross-dataset compatibility to support future research and policymaking
Comparison of international wind loading codes with a proposed Computational Fluid Dynamics framework considering the slenderness of buildings
No full textThis study compares the latest editions of five international wind loading codes -namely, the American code (ASCE 7–22), the Japanese code (AIJ-2019), the Australian/New Zealand code (AS/NZS 1170.2:2021), the European code (EN 1991-1-4:2018), and the Canadian code (NBCC 2020)- against a proposed Computational Fluid Dynamics (CFD) framework. The comparison is based on 12 isolated square buildings situated in open terrain, with height-to-plan-dimension ratios (H/B) ranging from 1 to 12. The objective is to classify each code according to the H/B ratio, identify its strengths and limitations, and highlight the scenarios where wind tunnel testing becomes essential. The influence of building natural frequency is also examined. Numerical results reveal that, for along-wind loads, ASCE 7–22 aligns well with CFD predictions for H/B ≤ 6, when the directionality factor is not considered. AIJ 2019 and NBCC 2020 show good agreement for H/B ≤ 8, AS/NZS 1170.2:2021 for H/B ≤ 5, and EN 1991-1-4:2018 for H/B ≥ 6. For across-wind base moments, AS/NZS 1170.2:2021 matches the CFD results well at H/B ratios of 3 and 4. In terms of acceleration, EN 1991-1-4:2018 provides the best match for along-wind acceleration, while NBCC 2020 performs best for cross-wind acceleration. Furthermore, the findings confirm the necessity of employing wind tunnel testing or a CFD-based approach when the building exceeds an H/B ratio of 4, as across-wind effects become dominant beyond this threshold
Large Eddy Simulation of Optimized Air Curtain Separation via Secondary Co-Flowing Jets
No full textUnconditioned air infiltration through frequently used entrance doors can degrade building energy performance, indoor air quality, and thermal comfort. Air curtains mitigate these effects and are also critical in smoke and dust control, cleanrooms, and cold rooms. Their performance is commonly expressed as separation efficiency, which depends on jet dynamics and entrainment. While most studies consider single-jet air curtains, this work investigates secondary co-flowing jets as a design strategy to reduce entrainment and enhance separation efficiency. Large eddy simulations (LES), validated against a dedicated particle image velocimetry (PIV) dataset of plane turbulent impinging co-flowing jets, assess the influence of key jet parameters: velocity ratio (R), secondary-jet width (W s ), and inter-jet spacing (d). The results indicate that incorporating secondary jets under suitable discharge conditions increases infiltration-based separation efficiency by up to 5.4 % without compromising the combined infiltration–exfiltration metric; the latter can also improve by up to 3 %. Given baseline efficiencies of 86.2 % (infiltration) and 78.7 % (combined) for an optimized single-jet curtain, these gains are significant
Access Repository Dashboard
Do you manage Heriot Watt Pure? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!