Software Model Research Articles

Effect of heat aging on pull-off strength of FRP epoxy bonded concrete: An experimental study and fire modelling

In this study, the bonding strengths of three different types of externally bonded composite systems were investigated under different environmental aging conditions at high temperatures, and the finite element model for a roof fire and concrete slab fire from above evaluated if the beams were externally reinforced with fiber-reinforced polymers (FRP). An FRP system is a structural reinforcement made of a type of fiber reinforcement fixed to a concrete surface through an epoxy adhesive. The bonding strength between the FRP and concrete substrates was measured using a pull-off test machine, as described in the EN 1542 standard. This study aims to determine the deterioration and negative effects of miscellaneous high temperatures on externally bonded FRPs used for strengthening civil structures. Epoxy-bonded carbon fiber-reinforced polymers (CFRP), glass fiber-reinforced polymers (GFRP), and basalt fiber-reinforced polymers (BFRP) were exposed to various temperatures of 23°C (control conditions), 70, 85, 100, 115, 130, and 150°C. Duratek® AV21 epoxy-based lamination system was used as an adhesive between the concrete and the FRP sheet. Three bonding failure modes (adhesive, cohesive, and substrate) were investigated for each test. The results were compared for three different types of FRPs under various temperatures, which is also significant research on the heat aging of the degradation process. The test results were also evaluated using finite element (FE) software modelling for roof and slab fires exposed from above, where the beams under the slab were reinforced with FRP systems. The test pull-off test results and FE model thermal analysis results were evaluated to obtain the temperature rise in the critical section of the concrete beam/slab in existing retrofitted buildings. The FE model results showed a critical temperature rise on the beam-slab corner connection as a result of the fire above the concrete slab. The duration of the FRP systems effectively bonded to the concrete beams located under different slab thicknesses and pull-off results were evaluated at elevated temperatures.

Modelling future land use land cover changes and their impacts on urban heat island intensity in Guangzhou, China

During rapid urbanization in developing countries, changes in land use and land cover (LULC) can significantly alter urban land surface temperatures (LST), exacerbating the urban heat island (UHI) effect and degrading the outdoor environment. In this study, taking Guangzhou, China, as an example, we used Landsat series satellite data from 1992 to 2022, classified the LULC of the study area by the Support Vector Machine (SVM) method, estimated the LST of the area by the mono-window algorithm, and classified the LST of the study area into five UHI intensity classes based on the normalized values of the LST, and explored the influence of the LULC on the distribution of the UHI intensity. The CA-ANN (cellular automata-artificial neural network) model in QGIS software was employed to forecast the distribution of LULC and UHI intensity in Guangzhou for 2032. The findings reveal a strong correlation between UHI intensity and LULC, with water bodies and vegetation primarily exhibiting low and sub-low temperatures, while urban areas exhibit sub-high and high temperatures. The prediction results show that, according to the current development trend, compared with 1992, the water body and vegetation cover in 2032 will decrease by 46.97% and 34.24%, the building land will increase by 263.71%, and the sub-high and high temperature areas will increase by 127.76% and 375.92%. By analysing the spatial and temporal changes in LULC and its relationship with the distribution of UHI intensity during urbanization, this study assists government administrations and urban planners in devising sensible urban development strategies and implementing effective measures to plan LULC rationally. This approach aims to mitigate the impacts of the urban heat island and foster sustainable urbanization.

Development and research of filter models communication and control systems configured for the required set of parameters

Problem statement. A digital filter refers to a hardware or software implementation of a mathematical algorithm that converts a digital signal in a certain way. The classification of digital filters is usually based on the functional characteristics of digital filtering algorithms. Digital filters may have parameters that cannot be implemented in analog filters, do not require periodic monitoring and calibration, and one filter can process several input channels or signals, while the accuracy is limited only by the bit depth used. The implementation of digital signal processing units using programmable logic integrated circuits (FPGAs) will significantly simplify hardware costs and make the most effective use of these digital filter capabilities. Goal. Conducting research in the field of digital signal processing in order to obtain fundamentally new software and hardware architectures, developing an RTL model of a complex functional block (SF block) of a digital signal processing system, its verification both at the logical and physical level. Results. In the course of the scientific research, a software and hardware model of the filter was developed to adjust the parameters during operation, taking into account their architectural advantages and disadvantages. In order to verify and confirm the adequacy of the methodology developed in the course of the study, an SF model was created-a digital signal processing unit. This model has been implemented and physically verified on the basis of a debugging board using FPGAs. Practical significance. The technique presented in this paper will allow the development of software and hardware devices for digital signal processing, with the possibility of their configuration at the software level for the required set of processing parameters, which in turn will significantly save resources spent on development.

Using software models of educational computers in studying computing tools organization and architecture

Using software models of educational computers in studying computing tools organization and architecture

Post-liquefaction settlement analysis of shallow foundations: numerical modeling and effective parameters

ABSTRACT This paper evaluates the seismic performance of shallow foundations located on liquefiable soil during seismic shaking and post-liquefaction using numerical analyses. Numerical simulations are performed using the UBCSAND constitutive model in FLAC software with validation against prior centrifuge tests conducted by the last author. The numerical analyses carried out in this study emphasize the post-seismic-liquefaction settlement of foundations which has not been addressed adequately compared with the co-seismic settlements. The effect of the foundation surcharge type, embedment depth, relative density, compaction depth, and foundation width are studied by a series of numerical parametric studies. The results show that soil densification and embedment depth can significantly affect the post-liquefaction-induced settlement of shallow foundations compared to the other simulated mitigation strategies. The results indicate that simultaneously considering both the relative density and the compaction depth ratio can significantly contribute to reducing post-liquefaction foundation settlement.

Abrasive Waterjet Machining.

The abrasive waterjet machining process was introduced in the 1980s as a new cutting tool; the process has the ability to cut almost any material. Currently, the AWJ process is used in many world-class factories, producing parts for use in daily life. A description of this process and its influencing parameters are first presented in this paper, along with process models for the AWJ tool itself and also for the jet-material interaction. The AWJ material removal process occurs through the high-velocity impact of abrasive particles, whose tips micromachine the material at the microscopic scale, with no thermal or mechanical adverse effects. The macro-characteristics of the cut surface, such as its taper, trailback, and waviness, are discussed, along with methods of improving the geometrical accuracy of the cut parts using these attributes. For example, dynamic angular compensation is used to correct for the taper and undercut in shape cutting. The surface finish is controlled by the cutting speed, hydraulic, and abrasive parameters using software and process models built into the controllers of CNC machines. In addition to shape cutting, edge trimming is presented, with a focus on the carbon fiber composites used in aircraft and automotive structures, where special AWJ tools and manipulators are used. Examples of the precision cutting of microelectronic and solar cell parts are discussed to describe the special techniques that are used, such as machine vision and vacuum-assist, which have been found to be essential to the integrity and accuracy of cut parts. The use of the AWJ machining process was extended to other applications, such as drilling, boring, milling, turning, and surface modification, which are presented in this paper as actual industrial applications. To demonstrate the versatility of the AWJ machining process, the data in this paper were selected to cover a wide range of materials, such as metal, glass, composites, and ceramics, and also a wide range of thicknesses, from 1 mm to 600 mm. The trends of Industry 4.0 and 5.0, AI, and IoT are also presented.

The Nature of Technical Debt in the Development of Descriptive Models for MBSE

AbstractModel‐Based Systems Engineering (MBSE) is the growing practice of systems engineering (SE) in which descriptive models replace documents as the embodiment of SE knowledge. These descriptive models capture SE information in place of documents, are developed in a similar manner to software source code, and are encoded and used in machine‐to‐machine applications as data. This paper describes how the Technical Debt concept widely used in the software domain—rework deferred to the future for expediency—needs to be modified for the domain of descriptive models. Technical Debt is often associated with agile development practices of software or descriptive models, which emphasize the rapid creation and iterative evolution of a Minimum Viable Product (MVP). Consciously applying appropriate modeling principles and practices is essential to make informed decisions during the modeling process to prevent the accumulation of excessive model Technical Debt—particularly during this iterative evolutionary process—which can require substantial rework to correct. The paper establishes a foundation for characterizing the Technical Debt implications of key model architecture and implementation decisions that are made explicitly or implicitly by modelers when developing descriptive models. To illustrate the model Technical Debt concept, several examples of modeling principles pertaining to model purpose and implementation are described along with their implications on model Technical Debt.

RadDeploy: A framework for integrating in-house developed software and artificial intelligence models seamlessly into radiotherapy workflows

The use of and research in automation and artificial intelligence (AI) in radiotherapy is moving with incredible pace. Many innovations do, however, not make it into the clinic. One technical reason for this may be the lack of a platform to deploy such software into clinical practice. We suggest RadDeploy as a framework for integrating containerized software in clinical workflows outside of treatment planning systems. RadDeploy supports multiple DICOM as input for model containers and can run model containers asynchronously across GPUs and computers. This technical note summarizes the inner workings of RadDeploy and demonstrates three use-cases with varying complexity.

Application of GO programming language for simulation of mass service processes

The subject matter of the article is methods and approaches to software modeling of System of Mass Services on the example of a multi-channel system with a limited queue and failures in case of its overflow. The goal of the work is to justify the feasibility of using modern computer information technologies, namely the Go programming language for modeling System of Mass Services. The following tasks were solved in the article: formulation of the researched System of Mass Services; determination of components, criteria of kinship of System of Mass Services with their software models; general overview of concurrency as a mathematical model; a description of the approaches and tools of the Go programming language. The following methods are used: Go programming language and its tools, concurrency, parallel execution. The following results were obtained: the researched task of mass service was formulated; criteria for comparing the components of System of Mass Services with the Go programming language toolkit were formed; an analysis of the feasibility of using the Go programming language for modeling System of Mass Services was carried out; received further development of tools for computer simulation of System of Mass Services; the application of concurrency approaches, their implementation in the Go programming language, to the modeling of System of Mass Services is proposed. Conclusions: The Go programming language is a very successful technology for modeling System of Mass Services. Its philosophy, way of working, as well as the built-in toolset provide ample opportunities for modeling various System of Mass Services. The use of this language is appropriate and allows to bring the behavior of the program closer to the simulated process, simplify implementation, and reduce the time required for data processing. There are great prospects for the further implementation of a software product implemented in the Go language in the field of mass service process modeling.

A Parallel Mediation Analysis of Behavioral Constructs Linking Intention-to-Use Technology to Performance Outcomes Among Pharmaceutical Executives

Managers in organizations are at a crossroads in understanding how behavioral intention to use technology influences employee performance. In the technology acceptance model, behavioral intention is a precursor to actual system use. However, there is inadequate information on how this intention indirectly impacts performance among employees in pharmaceutical organizations. Intuitively, behavioral mechanisms (job satisfaction, conscientiousness, self-efficacy, perceived relevance) should transform technology use into desired outcomes and serve as explanatory links between behavioral intention and technology performance. Using the theoretical lens of the technology acceptance model, reasoned action, and contingency theories, this study explored the mechanisms linking behavioral intention to technology performance among pharmaceutical executives. A web-based survey of a random sample of 282 pharmaceutical executives was conducted using a self-administered Google Forms questionnaire. Data was analyzed using variance-based structural equation modeling in ADANCO software, controlling for job-based demographics. All independent variables in the model significantly explained the variance in the dependent variable, technology performance. Perceived relevance was the only substantial linkage between behavioral intention and technology performance. The study confirmed that perceived relevance is an important mediator between behavioral intention and technology performance. To enhance performance, managers should adopt strategies that enhance job satisfaction, conscientiousness, self-efficacy, and perceived relevance. Ensuring appropriate technology deployment, adequate employee education, and targeted training are crucial for enhancing these mediating effects. The study contributes to the existing literature by recommending the inclusion of perceived relevance as a mediating link in the technology acceptance model.

MEASURING THICKNESS OF FLAX FIBRES IN A CLUSTER USING COMPUTER VISION

Authors analyse a method of indirect measurement of flax fibre linear density using its thickness, based on computer vision approach and “distance transform” algorithm in particular. A number of flaws of this method are identified. The main reason for the discrepancy is the effect of crossed fibres within the analysed sample. The secondary reason is the specific shape of fibre’s topological skeletonnear its tips. Based on these observations, a software model of the problem has been created. The software produces a simplified image of crossed fibres with specified properties, and measures this image using the above method. The effect of various factors on the discrepancy in the distribution of thickness values appears to match well with theoretical analysis. Additionally, a number of ways to improve the software model are outlined, related to how typicallyfibres are oriented within the analysed sample.

Stress-strain state of building structures taking into account possible local failure of the element

The issue of choosing a structural design and material for supporting structures is an important technical and economic task at the stage of developing a design solution. It depends on a number of factors: consequence class of the structure, reliability of the design solution, savings in basic building materials. The publication provides a classification of design schemes and types of load-bearing structures used in the corresponding solutions. The disadvantages and advantages of using prefabricated and monolithic structures for the installation and subsequent operation of the structural scheme of buildings and structures are considered. Modern design requirements include ensuring the ability of a damaged structure to adapt to new conditions while continuing to function while ensuring the integrity of human life, property and equipment. New conditions mean the consequences of the occurrence of a certain emergency situation, accompanied by weakening or overloading of the load-bearing structures of a structure or soil foundation: a change in the structural design, a combination of new existing loads and a redistribution of internal forces. The publication reflects the results of assessing the redistribution of the stress-strain state of the elements of the “base - foundations - load-bearing structures” system as a result of the implementation of a hypothetical emergency situation with the exclusion of the load-bearing structure from operation. The case of the collapse of one of the vertical load-bearing elements (local failure of the pylon) of an underground floor, which can be used as a dual-use structure, is considered. Calculations for the stability of the structure against progressive collapse were carried out by numerical modeling in the LIRA SAPR-2019 software using a quasi-static calculation and the method of direct integration of dynamics over time. It has been demonstrated that the method of numerical modeling the joint work of a building with a soil base affects the results of a calculation of the progressive collapse of the building frame. The influence of local collapse of a vertical load-bearing element on the redistribution of stresses and strains in the foundation structures of a building section is assessed. The load on the piles under the pylons around the element removed under the local failure scenario is expected to increase by 15...25%.

Kinetic Model Implementation of Fluidized Bed Devolatilization

Computational modeling is a powerful tool for studying and investigating the behavior of fluidized bed gasifiers and the modeling of the initial devolatilization step is necessary to provide a reliable description of the whole process involving the feedstock decomposition and the subsequent gasification reaction. In this work, a bench-scale fluidized bed reactor was used to examine the devolatilization of different carbonaceous materials within the temperature range from 650 to 850 °C. The experimental test campaign was used to derive the linear correlation factor to describe the devolatilization in terms of product distribution as a function of temperature and highlight the different behavior between lignocellulosic and plastic feedstocks. Furthermore, the experimental data were used to develop concise kinetic expressions able to fit the experimental devolatilization times ranging from 75 in the case of poplar at a lower temperature and 22 s for the Organic Fraction of Municipal Solid Waste (OFMSW) at a higher temperature. The obtained model produces a simple kinetic expression where the size of the particle is enclosed in the kinetic parameters. The kinetic model sided by the application of linear correlations describes the overall thermal decomposition in a fluidized bed, simplifying its modeling in commercial simulation software, even when particles are considered as point-like bodies.

Study on Sustainable Lightweight Design of Airport Waiting Chair Frame Structure Based on ANSYS Workbench

The airport waiting chair frames, as an important part of the overall seating, must be designed to provide comfort, safety, and aesthetic appeal. While the airport furniture industry has made progress in terms of sustainability, more efforts are needed to improve material selection, manufacturing processes, and supply chain management to support the development of sustainable furniture. This study proposes innovative ideas for the lightweight design of the frame, based on the limitations of the existing design. Firstly, structural innovations are discussed, non-traditional mesh panels and curved rounded designs are discussed, and non-introduced mesh panels and curved designs are used to enhance the strength and stability of airport waiting chairs and enhance their overall performance. Secondly, innovations in lightweighting have focused on adjusting the thickness dimensions to enhance comfort, material utilization, and sustainability as well as to achieve a lightweight and thin appearance effect. In order to determine the optimal ranges of values for the thickness of the seat surface support strip (P5), the thickness of the backrest strip (P3), and the thickness of the seat panel (P1), nine groups of chairs with different frame sizes were tested using an orthogonal experimental method. Based on the experimental results for size and topology optimization, NX2312 software modeling will be imported into ANSYS Workbench for static analysis. Using the optimized results, the use of 2.842 kg of steel was successfully reduced by 34.8% to ensure the seat’s stability. This provides a reference and idea for the digital and standardized innovative design of airport waiting chair furniture structure in the future. Through digital design and lightweight optimization, material savings and effective use of resources can be achieved, promoting the goal of sustainable development.

Evaluation of Nocturnal Aerosol Optical Depth Determining From a Lunar Photometry in Lanzhou of Northwest China

AbstractA Cimel Sun‐sky‐lunar photometer (CE318‐T) is designed to perform daytime and nighttime photometric measurements and calculate diurnal cycle of aerosol optical depth (AOD). Nevertheless, the determination of nocturnal AOD from CE318‐T requires a precise knowledge of extraterrestrial lunar irradiance, which significantly changes with moon's phase angle (MPA) and lunar libration in a single night. This study evaluated the 1‐year nocturnal AODs at Lanzhou by using three different methods, which were validated by collocated measurements of DIAL Lidar (as a reference) and Cimel software (as a proxy). The results indicated that three independent approaches could implement a similar performance to compute nocturnal AOD near full moon phase (i.e., MPA = 0°) under moderate aerosol loading. The spectral AOD values at nighttime calculated by ROLO Lunar Langley (Robotic Lunar Observatory model) and Sun‐moon Gain Factor (SMGF) methods are significantly underestimated under low moon's illumination or high MPA (MPA < −47° or MPA > 47°) and distinctly dependent on MPA. The RIMO correction factor (RCF) (ROLO Implementation for Moon photometry Observation correction factor) method could compensate the underestimated extraterrestrial lunar irradiances of ROLO model for about 6.76%–9.78%, and thus greatly improve the calculation accuracy of nighttime AOD. The day/night coherence transition test has demonstrated that we would obtain a good diurnal variation of AODs at Lanzhou after RCF correction. The overall averages of nocturnal AOD440nm differences between Cimel software and ROLO model and SMGF method are 0.064 ± 0.024 and 0.052 ± 0.022, respectively, while the corresponding difference of RCF is less than 0.021 ± 0.014 for all wavelengths, falling within uncertainty range of AERONET AOD products (∼±0.02). The diurnal variations of AODs determined from RCF method agree well with synchronous results of DIAL Lidar, with total mean AOD532nm differences of 0.038 ± 0.024 and 0.023 ± 0.017 in daytime and nighttime, respectively. The spectral AODs computed from RCF method are well consistent with Cimel software, although there are some discrepancies under low AOD cases (AOD440nm < 0.30), and the overall average of AOD440nm differences are less than −0.0053 ± 0.002 and −0.0185 ± 0.013 in daytime and nighttime, respectively. Our results confirmed that the CE318‐T photometer can be reasonably calculated nighttime AOD and Ångström exponent (AE440–870nm) at urban Lanzhou by using three independent methods, although the former two need to be greatly improved under low moon's illumination. The RCF method was proved to reliably calculate nocturnal AOD from moonlight irradiance, which didn't rely on MPA. A more accurate lunar irradiance model needs to be developed to improve the underestimation of current ROLO model. Long‐term climatological information of nocturnal AOD is crucial for comprehensively characterizing the diurnal variations of aerosol optical properties and atmospheric boundary layer structure during the winter at typical northern city of China, which deserves to be further investigated in the future.

Investigating the influence of erratic grid on stationary battery energy storage technologies in hybrid power systems: Techno-environ-economic perspectives

Several obstacles impede renewable energy penetration into the global energy sector. Amongst the apparent challenges which require credible research attention, is the selection of appropriate energy storage technologies in the context of intermittent renewable resources and frequent grid outages. Given these, the present study investigated the technical, economic, and environmental effects of an erratic national grid on four distinct battery technologies in hybrid wind, solar, and diesel energy systems. The study was conducted at Baze University Abuja, Nigeria using the Hybrid Optimization Model for Electric Renewables software. The battery types considered are vanadium redox flow battery (VRB), lead-acid battery, nickel-iron battery, and lithium-ion battery (LIB). The VRB-based hybrid energy systems demonstrated superior performances in meeting the electricity demands of the university at the lowest net present cost, levelized cost of energy, and carbon dioxide emissions of $6,328,003.00, $0.0722/kWh, and 21,754 kg/year respectively. This battery technology is characterized by storage depletion, throughput, and losses of 796 kWh/year, 406,570 kWh/year, and 182,757 kWh/year respectively. The sensitivity analysis showed that the frequency and duration of main grid outages affect the optimal systems’ economics, component sizes, battery energy losses, battery energy storage depletion, and renewable energy penetration.

Fuzzy Rule Based System of Optimal Pavement Maintenance and Rehabilitation Strategies for Yangon-Mandalay Expressway

Purpose: Systematic pavement management plays a vital role in the better Road Asset Management system. The lifespan of pavement can be preserved and prolonged by adequate maintenance measures in proper time. By early detection and repair of defects at initial stages with predictive maintenance reduces the rapid deterioration of the pavement. Moreover, inaccuracy in pavement deterioration prediction leads to an improper maintenance with wastage of time, cost and labor strength. To overcome all of these obstacles, this paper attempts an approach on optimal pavement maintenance strategy by means of fuzzy rule-based system. Materials and Methods: In this research, four pavement indicators of PCI, IRI, PSR and PSI have been taken into account as antecedents and five different types of pavement maintenance as consequents. In this research, ASTM D-6433, Road Lab Pro software, AASHTO guidelines and Fuzzy Logic (Mamdani) model have been used to evaluate the current pavement condition and optimal pavement maintenance strategies. Findings: According to research area, 130 total pavement sample units were undertaken to study for the mean pavement condition of PCI value 54.93 (poor), IRI 7.01 (fair), PSR 3.33 (fair) and PSI 3.35 (fair). Due to 13 years-old life span of traffic volume, temperature and other external factors, this expressway is suffering from potholes, bleeding, longitudinal and transverse cracking, weathering, joint reflection cracking for Asphalt Concrete (AC) overlay and linear cracking, joint seal failure, scaling, faulting, depression, lane/shoulder drop off for existing concrete pavement. According to the fuzzy logic model results, 42 numbers of fuzzy If-Then maintenance rules were verified as the most relevant pavement maintenance and rehabilitation strategies for Yangon-Mandalay Expressway. Implications to Theory, Practice and Policy: This research provide implications to the study and contributions to theory, practice and policy. This research paper insights into effective infrastructure maintenance and investment, emphasizing the role of advanced computational techniques in transportation economics. The key advantage of this research paper is to be effective, supportive, easy and accessible decision-making tool for transportation and pavement engineers, expressway planners and highways department authorities especially from developing countries.

Engineering recommender systems for modelling languages: concept, tool and evaluation

Recommender systems (RSs) are ubiquitous in all sorts of online applications, in areas like shopping, media broadcasting, travel and tourism, among many others. They are also common to help in software engineering tasks, including software modelling, where we are recently witnessing proposals to enrich modelling languages and environments with RSs. Modelling recommenders assist users in building models by suggesting items based on previous solutions to similar problems in the same domain. However, building a RS for a modelling language requires considerable effort and specialised knowledge. To alleviate this problem, we propose an automated, model-driven approach to create RSs for modelling languages. The approach provides a domain-specific language called Droid to configure every aspect of the RS: the type of the recommended modelling elements, the gathering and preprocessing of training data, the recommendation method, and the metrics used to evaluate the created RS. The RS so configured can be deployed as a service, and we offer out-of-the-box integration with Eclipse modelling editors. Moreover, the language is extensible with new data sources and recommendation methods. To assess the usefulness of our proposal, we report on two evaluations. The first one is an offline experiment measuring the precision, completeness and diversity of recommendations generated by several methods. The second is a user study – with 40 participants – to assess the perceived quality of the recommendations. The study also contributes with a novel evaluation methodology and metrics for RSs in model-driven engineering.

A survey of safety and trustworthiness of large language models through the lens of verification and validation

Large language models (LLMs) have exploded a new heatwave of AI for their ability to engage end-users in human-level conversations with detailed and articulate answers across many knowledge domains. In response to their fast adoption in many industrial applications, this survey concerns their safety and trustworthiness. First, we review known vulnerabilities and limitations of the LLMs, categorising them into inherent issues, attacks, and unintended bugs. Then, we consider if and how the Verification and Validation (V&V) techniques, which have been widely developed for traditional software and deep learning models such as convolutional neural networks as independent processes to check the alignment of their implementations against the specifications, can be integrated and further extended throughout the lifecycle of the LLMs to provide rigorous analysis to the safety and trustworthiness of LLMs and their applications. Specifically, we consider four complementary techniques: falsification and evaluation, verification, runtime monitoring, and regulations and ethical use. In total, 370+ references are considered to support the quick understanding of the safety and trustworthiness issues from the perspective of V&V. While intensive research has been conducted to identify the safety and trustworthiness issues, rigorous yet practical methods are called for to ensure the alignment of LLMs with safety and trustworthiness requirements.

Synthetic Optimization of Trafficability and Roll Stability for Off-Road Vehicles Based on Wheel-Hub Drive Motors and Semi-Active Suspension

Considering the requirements pertaining to the trafficability of off-road vehicles on rough roads, and since their roll stability deteriorates rapidly when turning violently or passing slant roads due to a high center of gravity (CG), an efficient anti-slip control (ASC) method with superior instantaneity and robustness, in conjunction with a rollover prevention algorithm, was proposed in this study. A nonlinear 14 DOF vehicle model was initially constructed in order to explain the dynamic coupling mechanism among the lateral motion, yaw motion and roll motion of vehicles. To acquire physical state changes and friction forces of the tires in real time, corrected LuGre tire models were utilized with the aid of resolvers and inertial sensors, and an adaptive sliding mode controller (ASMC) was designed to suppress each wheel’s slip ratio. In addition, a model predictive controller (MPC) was established to forecast rollover risk and roll moment in reaction to the change in the lateral forces as well as the different ground heights of the opposite wheels. During experimentation, the mutations of tire adhesion capacity were quickly discerned and the wheel-hub drive motors (WHDM) and ASC maintained the drive efficiency under different adhesion conditions. Finally, a hardware-in-the-loop (HIL) platform made up of the vehicle dynamic model in the dSPACE software, semi-active suspension (SAS), a vehicle control unit (VCU) and driver simulator was constructed, where the prediction and moving optimization of MPC was found to enhance roll stability effectively by reducing the length of roll arm when necessary.