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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A simulation‐based integrated virtual testbed for dynamic optimization in smart manufacturing systems

Abstract In a manufacturing system, production control‐related decision‐making activities occur at different levels. At the process level, one of the main control activities is to tune the parameters of individual manufacturing equipment. At the system level, the main activity is to coordinate production resources and to route parts to appropriate workstations based on their processing requirement, priority indices, and control policy. At the factory level, the goal is to plan and schedule the processing of parts at different operations for the entire system in order to optimize certain objectives. Note that the results of such activities at different levels are closely coupled and affect the overall performance of the manufacturing system as a whole. Therefore, it is important to systematically integrate these control and optimization activities into one unified platform to ensure the goal of each individual activity is aligned with the overall performance of the system. In this paper, we develop a simulation‐based virtual testbed that implements dynamic optimization, automatic information exchange, and decision‐making from the process‐level, system‐level, and factory‐level of a manufacturing system into an integrated computation environment. This is demonstrated by connecting a Python‐based numerical computation program, discrete‐event simulation software (Simul8), and an optimization solver (CPLEX) via a third‐party master program. The application of this simulation‐based virtual testbed is illustrated by a case study in a machining shop.

Sun, Yuting↗
DOE OSTI2013

Accelerating virtual high-throughput ligand docking: current technology and case study on a petascale supercomputer

In this paper, we give the current state of high-throughput virtual screening. We describe a case study of using a task-parallel Message Passing Interface version of AutoDock4 to run a virtual high-throughput screen of one million compounds on the Jaguar Cray XK6 Supercomputer at Oak Ridge National Laboratory. We include a description of scripts developed to increase the efficiency of the predocking file preparation and postdocking analysis. A detailed tutorial, scripts, and source code for this Message Passing Interface version of AutoDock4 are available online at http://www.bio.utk.edu/baudrylab/autodockmpi.htm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

VinaMPI: Facilitating multiple receptor high-throughput virtual docking on high-performance computers

The program VinaMPI has been developed to enable massively large virtual drug screens on leadership-class computing resources, using a large number of cores to decrease the time-to-completion of the screen. VinaMPI is a massively parallel Message Passing Interface (MPI) program based on the multithreaded virtual docking program AutodockVina, and is used to distribute tasks while multithreading is used to speed-up individual docking tasks. VinaMPI uses a distribution scheme in which tasks are evenly distributed to the workers based on the complexity of each task, as defined by the number of rotatable bonds in each chemical compound investigated. VinaMPI efficiently handles multiple proteins in a ligand screen, allowing for high-throughput inverse docking that presents new opportunities for improving the efficiency of the drug discovery pipeline. VinaMPI successfully ran on 84,672 cores with a continual decrease in job completion time with increasing core count. The ratio of the number of tasks in a screening to the number of workers should be at least around 100 in order to have a good load balance and an optimal job completion time. The code is freely available and downloadable. Lastly, the instructions for downloading and using the code are provided in the Supporting Information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The 2024 “Hacking Limnology” Workshop Series and Virtual Summit: Increasing Inclusion, Participation, and Representation in the Aquatic Sciences

The 4th Aquatic Ecosystem MOdeling Network—Junior (AEMON-J) Hacking Limnology Workshop and 5th Virtual Summit: Incorporating Data Science and Open Science in the Aquatic Sciences (DSOS) convened 15–19 July 2024. During the week, these joint communities engaged in activities at the intersection of big data, open science, modeling, remote sensing, and the aquatic sciences. The weeklong event, with over 100 aquatic science practitioners and enthusiasts, followed a similar structure to previous years, comprising three days of workshops followed by two days of the virtual summit.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The 2025 “Hacking Limnology” Workshop Series and DSOS Virtual Summit: A Half Decade of Data‐Intensive Aquatic Science

The 5th Aquatic Ecosystem MOdeling Network—Junior (AEMON-J) “Hacking Limnology” Workshop and 6th Virtual Summit: Incorporating Data Science and Open Science in the Aquatic Sciences (DSOS) convened 21–25 July 2025. As in previous years (Fig. 1; Meyer and Zwart 2020; Meyer et al. 2021b, 2021c, 2022, 2024), the virtual workshops and summit were free of charge, the content was formatted to allow for broad engagement from a globally distributed audience, and workshop materials and recordings were made available on the AEMON-J/DSOS archive (Meyer et al. 2021a). In contrast to previous years, which primarily focused on inland aquatic ecosystems, this year's workshops and summit showcased a notable plurality of ecosystem types, with workshops spanning marine, riverine, and lacustrine environments. The weeklong event brought together researchers and practitioners interested in the nexus of data science, open science, and the aquatic sciences, hosting between 47 and 65 attendees at a single time and a higher number of registrants (n = 389), who might opt to access the material asynchronously.

Meyer, Michael F. [US Geological Survey, Portland,↗
DOE OSTI2020

The arbitrary‐order virtual element method for linear elastodynamics models: convergence, stability and dispersion‐dissipation analysis

Abstract We design the conforming virtual element method for the numerical approximation of the two‐dimensional elastodynamics problem. We prove stability and convergence of the semidiscrete approximation and derive optimal error estimates under h ‐ and p ‐refinement in both the energy and the L 2 norms. The performance of the proposed virtual element method is assessed on a set of different computational meshes, including nonconvex cells up to order four in the h ‐refinement setting. Exponential convergence is also experimentally observed under p ‐refinement. Finally, we present a dispersion‐dissipation analysis for both the semidiscrete and fully discrete schemes, showing that polygonal meshes behave as classical simplicial/quadrilateral grids in terms of dispersion‐dissipation properties.

Antonietti, Paola F.↗
DOE OSTI2024

Numerical integration in the virtual element method with the scaled boundary cubature scheme

Abstract The virtual element method (VEM) is a stabilized Galerkin method on meshes that consist of arbitrary (convex and nonconvex) polygonal and polyhedral elements. A crucial ingredient in the implementation of low‐ and high‐order VEM is the numerical integration of monomials and nonpolynomial functions over such elements. In this article, we apply the recently proposed scaled boundary cubature (SBC) scheme to compute the weak form integrals in various virtual element formulations over polygonal and polyhedral meshes. In doing so, we demonstrate the flexibility of the approach and the accuracy that it delivers on a broad suite of boundary‐value problems in 2D and 3D over polytopes with affine faces as well as on elements with curved boundaries. In addition, the use of the SBC scheme is exemplified in an enriched Poisson formulation of the VEM in which weakly singular functions are required to be integrated. This study establishes the SBC method as a simple, accurate and efficient integration scheme for use in the VEM.

Chin, Eric B.↗
DOE OSTI2018

An Event Detection Framework for Virtual Observation System: Anomaly Identification for an ACME Land Simulation

Based on previous work on in-situ data transfer infrastructure and compiler-based software analysis, we have designed a virtual observation system for real time computer simulations. This paper presents an event detection framework for a virtual observation system. By using signal processing and detection approaches to the memory-based data streams, this framework can be reconfigured to capture high-frequency events and low-frequency events. These approaches used in the framework can dramatically reduce the data transfer needed for in-situ data analysis (between distributed computing nodes or between the CPU/GPU nodes). In the paper, we also use a terrestrial ecosystem system simulation within the Earth System Model to demonstrate the practical values of this effort.

Yao, Cindy↗
DOE OSTI2025

Threshold resummation for double-deeply virtual Compton scattering

The threshold region for double-deeply virtual Compton scattering (DDVCS) is discussed. I derive a resummation formula for the (partonic) threshold logarithms in the flavor non-singlet case. The resummations can be done by using (re)factorization theorems for the coefficient functions near the partonic thresholds. As a byproduct, we obtain the leading term in the threshold limit of the two-loop coefficient function in double-deeply-virtual Compton scattering, which agrees with the recent result from explicit calculation, providing a highly non-trivial cross-check.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Virtual monoenergetic reconstruction of contrast-enhanced CT scans of the abdomen and pelvis at 40 keV improves the detection of peritoneal metastatic deposits

Purpose: To evaluate the role of virtual monoenergetic imaging (VMI) in the detection of peritoneal metastatic disease in contrast-enhanced computed tomography (CT) of the abdomen and pelvis and to compare this technique to the conventional 120 kV mixed dataset. Materials and methods: Institutional review board approval was obtained with no informed consent required for this retrospective analysis. 43 consecutive patients with histopathologically confirmed peritoneal disease were scanned using a standard protocol on a 128-section dual-source, dual-energy CT system (100/140 keV). Scans were retrospectively reconstructed at VMI energy levels from 40–110 keV in 10 keV increments and were analyzed both quantitatively and qualitatively. CNR values for peritoneal metastatic deposits were recorded using region of interest (ROI) analysis at each energy level for all VMI datasets. Subjective analysis was performed by two independent fellowship-trained readers with combined experience of greater than 15 years. Qualitative parameters included diagnostic acceptability, subjective noise, and contrast resolution and confidence. Results: The contrast-to-noise ratios (CNRs) for peritoneal metastatic deposits at the different VMI energy levels were compared using a one-way ANOVA with Tukey Post Test, and the optimal CNR was observed at 40 keV (p < 0.0001). Qualitative parameters were compared using a Paired T Test. Subjective noise, diagnostic acceptability, and contrast resolution was significantly better on the conventional images, but readers reported increased confidence on VMI at 40 keV (p < 0.001). Conclusion: VMI reconstruction of contrast-enhanced dual-energy CT scans of the abdomen and pelvis at 40 keV maximizes the conspicuity of metastatic peritoneal deposits and improves radiologists’ diagnostic confidence compared with conventional CT images. We recommend using virtual monoenergetic datasets at 40 keV as a tool for improving the detection of these lesions in routine clinical practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Utility of the Virtual Liver Parenchymal Perfusion Area Using a Commercially Available Workstation in Transarterial Chemoembolization for Hepatocellular Carcinoma

Purpose: To evaluate the accuracy of the virtual liver parenchymal perfusion area using a commercially available workstation and liver analysis software in conventional transarterial chemoembolization (cTACE) for hepatocellular carcinoma (HCC). Materials and Methods: This method was retrospectively applied to 29 treated HCCs in 23 patients. The virtual embolic area (VEA) was estimated based on cone beam computed tomography during hepatic arteriography using a commercially available workstation and liver analysis software by two observer groups (group A: experts; group B: semi-experts). The real embolic area (REA) was defined as the area where iodized oil accumulated on computed tomography at 1 week after cTACE. The REA was estimated by each of the two groups, and the mean REA between the groups (mREA) was used as a standard reference. Agreement of volume and cross-sectional area in three orthogonal planes between the VEA and mREA were analyzed using intraclass correlation coefficients (ICCs) and Bland–Altman plots. Results: The ICCs for volume between VEA and mREA were 0.97 and 0.88 for groups A and B, respectively, and those for cross-sectional area were 0.94 and 0.88 for the axial plane, 0.95 and 0.83 for the coronal plane, and 0.87 and 0.74 for the sagittal plane, respectively. Thus, the overall agreement was excellent, except for the sagittal imaging plane in group B. Conclusion: This method using a commercially available workstation and liver analysis software can be useful for estimating the embolic area in cTACE.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Force Sensing in Nanoscale: Integration of Virtual Spring for Sensing the Interactions of β-Amyloid Grabbed by Prefoldin

Analysis of atomic forces in molecular scale including the reciprocal internal force directions, quantity, and Young’s modulus, and more detailed analysis via diagrams, is one of the most current research topics. This research aims to analyze the bilateral forces applied between a nano-actuator and a cargo from a new perspective. While virtual springs have been used as a tool to convey forces in the previous steered molecular dynamics simulations, this study uses the spring as a sensor for measuring the internal forces. This study introduces atomic sensing via the steered molecular dynamics method. Following the previous studies, the protein employed in this study is the mutated Archetype Prefoldin being used to control the pathogenic cargo beta-amyloid (Alzheimer’s). The powerful Gromacs software carries out the simulations for the calculation of the total force and force for each branch. The simulation results illustrate the total force between the cargo and nano-actuator is ~ 2.8 nN, while each branch needs a force of ~ 1.2–1.5 nN to release the cargo. The results demonstrate the validity of the method and applicability of the virtual sensor for assessing the microscopic forces. This investigation is a pioneer study for the advent of the sensor as an assessment tool for the mechanical analysis and precise atomic force studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Propagation of Noise Uncertainty Through Virtual Strain Gauge Formulations for 2D Digital Image Correlation

The effect of displacement uncertainty is examined on 2-dimensional strain, calculated using linear surfaces fitted to the displacement field. A classical engineering error propagation method is used to calculate uncertainty in Green-Lagrangian strain calculations. The derived uncertainty is compared to a Monte Carlo simulation and discrepancies under 2% are seen between these two methods. The effect of virtual strain gauge size, displacement uncertainty, and boundaries on the region of interest on the strain uncertainty are considered. Here, an exponential decay relationship is observed between strain uncertainty and virtual strain gauge size, while a linear relationship is seen between strain and displacement uncertainty. For boundaries in the region of interest, strain uncertainty is affected by the reduced number of points available to perform the regression.

42 ENGINEERING↗
DOE OSTI2021

Water transport properties of virtual fractal porous media: Implications for the unsaturated transport properties of cement-based materials

Cement-based materials are more and more recognized as fractal materials. From a practical point of view, fractality means that the pore size distribution can be described using fractal scaling law (i.e. power functions). Here, the simplest scaling law making use of a single fractal dimension was used to generate simple and virtual fractal porous media (based on bundles of parallel cylindrical pores). The capillary curve and permeability (relative and intrinsic) of the virtual porous media were then estimated through theoretical and numerical approaches. The results show that: (1) although bereft of any physical basis, van Genuchten equation bears some fractal information; (2) although highly flexible, van Genuchten equation fails to perfectly fit the capillary curves and can thus generate error in inverse analysis (for intrinsic permeability evaluation) and (3) there seems to be a relation between the intrinsic permeability and van Genuchten pressure parameter.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Virtual Model Validation of Complex Multiscale Systems: Applications to Nonlinear Elastostatics

We propose a virtual statistical validation process as an aid to the design of experiments for the validation of phenomenological models of the behavior of material bodies, with focus on those cases in which knowledge of the fabrication process used to manufacture the body can provide information on the micro-molecular-scale properties underlying macroscale behavior. One example is given by models of elastomeric solids fabricated using polymerization processes. We describe a framework for model validation that involves Bayesian updates of parameters in statistical calibration and validation phases. The process enables the quanti cation of uncertainty in quantities of interest (QoIs) and the determination of model consistency using tools of statistical information theory. We assert that microscale information drawn from molecular models of the fabrication of the body provides a valuable source of prior information on parameters as well as a means for estimating model bias and designing virtual validation experiments to provide information gain over calibration posteriors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Extension of a Virtual Refrigerant Charge Sensor

The primary goal of the work described in this paper was to evaluate and extend a virtual refrigerant charge sensor (VRC) for determining refrigerant charge for equipment having variable-speed compressors and fans. To evaluate the accuracy of the VRC, data were first collected from previous laboratory tests for different systems and over a wide range of operating conditions. In addition, new laboratory tests were performed to consider conditions not available within the existing data set. The systems for the new laboratory tests were two residential ductless split heat pump systems that employ a variable-speed compressor and R-410a as the refrigerant. Based on the evaluations, the original virtual charge sensor (termed model I) was found to work well in estimating the refrigerant charge for systems with a variable-speed compressor under many operating conditions. However, for extreme test conditions such as low outdoor temperatures and low compressor speed, the VRC needed to be improved. To overcome the limitations, the model associated with the VRC sensor was modified to include a term involving the inlet quality to the evaporator estimated from the condenser outlet condition (termed model II). Both model I and II showed good performance in terms of predicting charge levels for systems with a constant speed compressor, but model II gave better performance for systems with a variable-speed compressor. However, when the superheat of the compressor was zero, neither model I nor II could accurately predict charge level. Therefore, a third approach (Model III) was developed that includes the discharge superheat of the compressor. This model improved performance for a laboratory-tested system that included a number of points with no superheat entering the compressor.

Kim, Woohyun↗