AnalogSim: a Modeling Framework for SRAM-based Analog In-Memory Computing

Computational decision framework for enhancing resilience of the energy, water and food nexus in risky environments

Computer model coupling hemodynamics and oxygen transport in the coronary capillary network: Pulsatile vs. non-pulsatile analysis

Via Granular Computing (GrC), one can create effective computational frameworks for obtaining information from data, motivated by the human perception of combining similar objects. Combining knowledge gained via GrC with a Fuzzy inference engine (Neural‐Fuzzy) enable us to develop a transparent system. While weighting variables based on their importance during the iterative data granulation process has been proposed before (W‐GrC), there is no work in the literature to demonstrate effectiveness and impact on Type‐2 Fuzzy Logic systems (T2‐FLS). The main contribution of this paper is to extend W‐GrC, for the first time, to both Type‐1 and Type‐2 models known as Radial Basis Function Neural Network (RBFNN) and General Type‐2 Radial Basis Function Neural Network (GT2‐RBFNN). The proposed framework is validated using popular datasets: Iris, Wine, Breast Cancer, Heart and Cardiotocography. Results show that with the appropriate selection of feature weight parameter, the new computational framework achieves better classification accuracy outcomes. In addition, we also introduce in this research work an investigation on the modelling structure's interpretability (via Nauck's index) where it is shown that a good balance of interpretability and accuracy can be maintained.

: The Individual System/Organization Cost (ISOC) Model was devised for the rapid costing of a large number of alternative systems or organizations. The ISOC Model is a flexible IBM 7040 FORTRAN IV computer framework to which a variety of individual system or organization cost models may be adapted for use in cost studies requiring numerous calculations that cannot be performed conveniently by hand. This paper is an introduction to the ISOC Model. The basic features of the model and the general procedures for its operation are described. An example is provided on the adaptation of a specific cost model, the surveillance Aircraft System Cost Model, to the computer framework of the ISOC Model. Fictitious data values for two hypothetical surveillance-aircraft systems illustrate procedures for translating data requirements for a specific cost model into a form usable in the ISOC Model. In actual practice the configuration of the ISOC Model will vary according to the costing problem to which it is applied.

Cardiovascular diseases are the leading cause of death worldwide, with coronary heart disease (CHD) being the most prevalent form. Advances in computational frameworks and digital twin technology have redefined vascular modeling, providing new opportunities for understanding disease progression and improving personalized treatment strategies. This study presents a high-performance computational framework for automated 3D vascular modeling and quantitative analysis, addressing key limitations of existing methods, such as reproducibility, scalability, and computational efficiency. The framework integrates parametric computer-aided diagnosis (CAD) modeling with automated data processing to streamline 3D model generation from imaging data, ensuring rapid and reproducible results at scale. It automates key processes such as surface reconstruction, metric extraction, and geometry optimization, minimizing manual intervention and enabling high-throughput analysis. Validation confirmed the accuracy and consistency of the reconstructed geometries, with minimal deviations in key measurements. The framework's modular design and support for standardized data formats allow seamless integration with computational workflows. By improving scalability and reducing computational demands, the proposed system supports population-scale studies, predictive modeling, and in silico clinical trials, offering a robust tool for advancing precision medicine and computational cardiovascular research.

Bridges are vulnerable to the fatigue damage accumulation caused by traffic loading over the service period. A continuous growth in both the vehicle weight and the traffic volume may cause a safety hazard to existing bridges. This study presented a computational framework for probabilistic modeling of the fatigue damage accumulation of short to medium span bridges under actual traffic loading. Stochastic truck-load models were simulated based on site-specific weigh-in-motion measurements. A response surface method was utilized to substitute the time-consuming finite element model for an efficient computation. A case study of a simply supported bridge demonstrated the effectiveness of the computational framework. Numerical results show that the simulated fatigue stress spectrum captures the probability density functions of the heavy traffic loading. The equivalent fatigue stress range increases mostly linearly in the good road roughness condition with the growth of the gross vehicle weight. The vehicle typ...

Biomembranes play a central role in various phenomena like locomotion of cells, cell-cell interactions, packaging and transport of nutrients, transmission of nerve impulses, and in maintaining organelle morphology and functionality. During these processes, the membranes undergo significant morphological changes through deformation, scission, and fusion. Modelling the underlying mechanics of such morphological changes has traditionally relied on reduced order axisymmetric representations of membrane geometry and deformation. Axisymmetric representations, while robust and extensively deployed, suffer from their inability to model-symmetry breaking deformations and structural bifurcations. To address this limitation, a three-dimensional computational mechanics framework for high fidelity modelling of biomembrane deformation is presented. The proposed framework brings together Kirchhoff–Love thin-shell kinematics, Helfrich-energy-based mechanics, and state-of-the-art numerical techniques for modelling deformation of surface geometries. Lipid bilayers are represented as spline-based surface discretizations immersed in a three-dimensional space; this enables modelling of a wide spectrum of membrane geometries, boundary conditions, and deformations that are physically admissible in a three-dimensional space. The mathematical basis of the framework and its numerical machinery are presented, and their utility is demonstrated by modelling three classical, yet non-trivial, membrane deformation problems: formation of tubular shapes and their lateral constriction, Piezo1-induced membrane footprint generation and gating response, and the budding of membranes by protein coats during endocytosis. For each problem, the full three-dimensional membrane deformation is captured, potential symmetry-breaking deformation paths identified, and various case studies of boundary and load conditions are presented. Using the endocytic vesicle budding as a case study, we also present a ‘phase diagram’ for its symmetric and broken-symmetry states.

This paper presents a critical review of the current challenges in analyzing large, realistic pile groups in soft clay soil under earthquake shaking. The review focuses on three main essentials of numerical analyses, namely soil behavior and constitutive model, pile and pile-soil interface modeling and computational framework.

Competitive Food Supply Chain Networks with Application to Fresh Produce

Aircraft concepts of tomorrow, such as high aspect ratio wing aircraft, are far more integrated between technical disciplines and thus require multidisciplinary design approaches. Design tools able to predict associated dynamics need to be developed if such wing concepts are to be matured for use on future transport aircraft. The Cranfield University Beam Reduction and Dynamic Scaling ( BeaRDS) Programme provides a framework that scales a conceptual full size aircraft to a cantilevered wing model of wind tunnel dimensions, such that there is similitude between the static and dynamic behaviour of the model and the full size aircraft. This process of aeroelastically scaled testing combines the technical disciplines of aerodynamics, flight mechanics and structural dynamics, to provide a means by which future concept aircraft can be de-risked and explored . Data acquisition from wind tunnel testing can then be used to validate fluid-structure interaction frameworks that model the aeroelastic effect on the flight dynamics of the aircraft. This paper provides an overview of the BeaRDS methodology, and focuses on the Phase I of the programme, being the development of a reduced Cranfield A-13 aircraft cantilevered wing, to mitigate risk associated with the manufacturing and instrumentation app roach. It is shown that a low cost acquisition system of commercial Inertial Measurement Units (IMUs) can measure the response of the wing within the desired frequency range. Issues associated with the Phase I testing are discussed, and methods are proposed for the Phase II programme that allow these problems to be resolved for a larger scale flexible wing with active control surfaces.

Lever-propelled wheelchairs constitute a promising alternative to their handrim-propelled counterparts as they are associated with more favorable upper extremity biomechanics during propulsion. This can potentially reduce the large incidence of upper extremity pain and injury among long-term users of handrim-propelled wheelchairs. However, the effects of wheelchair design parameters on locomotion performance are poorly understood. Here, we propose a modeling approach and an optimal control framework to investigate the influence of parameters such as lever length, gear ratio, and position of the lever pivot on steady-state locomotion performance. We propose using a pair of equivalent antagonistic muscle units, called Equivalent Muscle Actuators (EMAs), acting directly on the propulsion levers and representing the intrinsic properties of the musculoskeletal system and its interaction with the device. This approach reduces the model dimension and promotes a straightforward analysis of the biomechanical advantage considering the human-device interaction. The predictive simulations of wheelchair locomotion are generated for various gear ratios and lever pivot positions at different average velocities, slope angles, and hand positions along the lever. The results reveal that a posterior pivot position requires consistently less effort due to a biomechanically more favorable configuration and gravity’s beneficial effect during the propulsion phase. The results also indicate the most appropriate gear ratios depending on speed and slope angle. This study provides guidelines for the design of lever-propelled wheelchairs and a modeling and computational framework that can be extended to investigate different assistive technologies or other mechanical devices interacting with the human body.

With the rapid development of e-commerce over Internet, web services have attracted much attention in recent years. Nowadays, enterprises are able to outsource their internal business processes as services and make them accessible via the Web. Then they can dynamically combine individual services to provide new value-added services. With the increasing number of web services having equivalent functionality, the binding procedure is driven by some non-functional, Quality of Service (QoS) criteria, such as the money cost, response time, reputation, reliability or a trade-off between them. Thus, an important problem is, given QoS constraints, how to aggregate and leverage individual service’s QoS information to derive the optimal QoS of the composite service. In this paper, we propose a novel QoS model for performing flexible service selection. The key idea of the model is to relax users’ QoS constraints and try to find the most possible services satisfying users’ QoS requirements. Based on the proposed QoS framework, we develop various algorithms for making service selection on individual and composite services. We also introduce a top-k ranking strategy to reflect a user’s personalized requirements. Experimental evaluation shows the proposed QoS model is efficient and practical.

An aneurysm is a medical condition where a section of the artery bulges out under high pressure. Patients suffering from aneurysm rupture have a mortality rate of around 20% and a morbidity rate of up to 40%. The present imaging methods, such as MRI and CT scans, only offer geometrical information on the aneurysm and cannot predict the risk of rupture associated with its progression. To address this gap, a novel computational modeling framework was developed to describe aneurysm growth and analyze the rupture risk under varying pressure loading conditions. The aneurysms were modeled at the vulnerable posterior cerebral artery (PCA) and posterior communicating artery (PCoA), extracted using image segmentation. Five different aneurysm diameters and two wall thicknesses were considered to simulate different phases of aneurysm progression. The realistic pressure loadings on the posterior cerebral arteries were described using three pressures (diastolic, systolic, and hypertensive), and the stress distributions across all models were evaluated to estimate the rupture risk. For PCA, the value of max. von-Mises stress varied between 5.334 MPa and 13.324 MPa for different models with wall thickness of 0.05 mm and from 2.579 MPa to 7.582 MPa for 0.1 mm wall thickness models. For PCoA, the value of max. von-Mises stress ranged from 2.073 MPa to 11.383 MPa for artery-aneurysm models with 0.075 mm thickness and from 2.817 MPa to 10.779 MPa for artery-aneurysm models with 0.15 mm thickness. It was found that the stress values on the aneurysm walls significantly varies with change in blood pressure and aneurysm diameter. An aneurysm with a large diameter and thin wall was also observed to pose a significant risk of rupture, particularly at high blood pressures. These results are expected to provide valuable information to the medical practitioners and help in the prediction of rupture risks using image analysis of aneurysm size and in making timely treatment decisions. Statement of SignificanceThe points of significance of our work are:•A novel computational modeling framework to evaluate the aneurysm growth and analyze the rupture risk.•The realistic pressure loadings conditions (i.e., diastolic, systolic, and hypertensive) of the cardiac cycle were considered and the stress distributions were evaluated to estimate the rupture risk.•To date, such extensive research on cerebral aneurysms has not been reported. The results are anticipated to provide valuable information to the medical practitioners in predicting the rupture risks using structural parameters of the aneurysm.

PurposeExternal cardiac assist devices are based on a promising and simple concept for treating heart failure, but they are surprisingly difficult to design. Thus, a structured approach combining experiments with computer-based optimization is essential. The latter provides the motivation for the work presented in this paper.MethodsWe present a computational modeling framework for realistic representation of the heart’s tissue structure, electrophysiology and actuation. The passive heart tissue is described by a nonlinear anisotropic material law, considering fiber and sheetlet directions. For muscle contraction, an orthotropic active-strain model is employed, initiated by a periodically propagating electrical potential. The model allows for boundary conditions at the epicardium accounting for external assist devices, and it is coupled to a circulation network providing appropriate pressure boundary conditions inside the ventricles.ResultsSimulated results from an unsupported healthy and a pathological heart model are presented and reproduce accurate deformations compared to phenomenological measurements. Moreover, cardiac output and ventricular pressure signals are in good agreement too. By investigating the impact of applying an exemplary external actuation to the pathological heart model, it shows that cardiac patches can restore a healthy blood flow.ConclusionWe demonstrate that the devised computational modeling framework is capable of predicting characteristic trends (e.g. apex shortening, wall thickening and apex twisting) of a healthy heart, and that it can be used to study pathological hearts and external activation thereof.

As CPU frequency and computing power grow fast, conventional Von Neumann architecture is suffering from more and more severe data transfer latency and power consumption between CPU and DRAM, known as memory wall problem. In this paper, we propose a novel near memory architecture based on the H-tree architecture of DRAM to decrease the data transfer latency. There are three work modes in the proposed CoDRAM, GMM (General Main Memory Mode), ACM (Auxiliary Computing Mode) and PCM (Parallel Computing Mode). Compared with conventional CPU+DRAM architecture, the experiment shows that the proposed CoDRAM computing framework can improve about 20% and 33% performance on matrix addition and integral image computing in ACM mode. And in PCM mode, the improvement is about 15× and 3× in matrix addition and integral image computing. Meanwhile, the overhead in GMM mode is only about 1%.