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DOE OSTI2022

Calibration and Validation of a Mechanistic COVID-19 Model for Translational Quantitative Systems Pharmacology – A Proof-of-Concept Model Development for Remdesivir

With the ongoing global pandemic of coronavirus disease 2019 (COVID-19), there is an urgent need to accelerate the traditional drug development process. Many studies identified potential COVID-19 therapies based on promising nonclinical data. However, the poor translatability from nonclinical to clinical settings has led to failures of many of these drug candidates in the clinical phase. In this study, we propose a mechanism-based, quantitative framework to translate nonclinical findings to clinical outcome. Adopting a modularized approach, this framework includes an in silico disease model for COVID-19 (virus infection and human immune responses) and a pharmacological component for COVID-19 therapies. Here, the disease model was able to reproduce important longitudinal clinical data for patients with mild and severe COVID-19, including viral titer, key immunological cytokines, antibody responses, and time courses of lymphopenia. Using remdesivir as a proof-of-concept example of model development for the pharmacological component, we developed a pharmacological model that describes the conversion of intravenously administered remdesivir as a prodrug to its active metabolite nucleoside triphosphate through intracellular metabolism and connected it to the COVID-19 disease model. After being calibrated with the placebo arm data, our model was independently and quantitatively able to predict the primary endpoint (time to recovery) of the remdesivir clinical study, Adaptive Covid-19 Clinical Trial (ACTT). Our work demonstrates the possibility of quantitatively predicting clinical outcome based on nonclinical data and mechanistic understanding of the disease and provides a modularized framework to aid in candidate drug selection and clinical trial design for COVID-19 therapeutics.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2023

Data-constrained Solar Modeling with GX Simulator

To facilitate the study of solarflares and active regions, we have created a modeling framework, the freelydistributed GX Simulator IDL package, that combines 3D magnetic and plasma structures with thermal andnonthermal models of the chromosphere, transition region, and corona. Its object-based modular architecture,which runs on Windows, Mac, and Unix/Linux platforms, offers the ability to either import 3D density andtemperature distribution models, or to assign numerically defined coronal or chromospheric temperatures anddensities, or their distributions, to each individual voxel. GX Simulator can apply parametric heating modelsinvolving average properties of the magneticfield lines crossing a given voxel, as well as compute and investigatethe spatial and spectral properties of radio,(sub)millimeter, EUV, and X-ray emissions calculated from the model,and quantitatively compare them with observations. The package includes a fully automatic model productionpipeline that, based on minimal users input, downloads the required SDO/HMI vector magneticfield data,performs potential or nonlinear force-freefield extrapolations, populates the magneticfield skeleton withparameterized heated plasma coronal models that assume either steady-state or impulsive plasma heating, andgenerates non-LTE density and temperature distribution models of the chromosphere that are constrained byphotospheric measurements. The standardized models produced by this pipeline may be further customizedthrough specialized IDL scripts, or a set of interactive tools provided by the graphical user interface. Here, wedescribe the GX Simulator framework and its applications.

Solar active regions↗

DOE OSTI2018

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment

Here, a working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide “bottom-up” mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a “top-down” approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

NASA Tech Briefs, July 2010

Topics covered include: Wirelessly Interrogated Wear or Temperature Sensors; Processing Nanostructured Sensors Using Microfabrication Techniques; Optical Pointing Sensor; Radio-Frequency Tank Eigenmode Sensor for Propellant Quantity Gauging; High-Temperature Optical Sensor; Integral Battery Power Limiting Circuit for Intrinsically Safe Applications; Configurable Multi-Purpose Processor; Squeezing Alters Frequency Tuning of WGM Optical Resonator; Automated Computer Access Request System; Range Safety for an Autonomous Flight Safety System; Fast and Easy Searching of Files in Unisys 2200 Computers; Parachute Drag Model; Evolutionary Scheduler for the Deep Space Network; Modular Habitats Comprising Rigid and Inflatable Modules; More About N2O-Based Propulsion and Breathable-Gas Systems; Ultrasonic/Sonic Rotary-Hammer Drills; Miniature Piezoelectric Shaker for Distribution of Unconsolidated Samples to Instrument Cells; Lunar Soil Particle Separator; Advanced Aerobots for Scientific Exploration; Miniature Bioreactor System for Long-Term Cell Culture; Electrochemical Detection of Multiple Bioprocess Analytes; Fabrication and Modification of Nanoporous Silicon Particles; High-Altitude Hydration System; Photon Counting Using Edge-Detection Algorithm; Holographic Vortex Coronagraph; Optical Structural Health Monitoring Device; Fuel-Cell Power Source Based on Onboard Rocket Propellants; Polar Lunar Regions: Exploiting Natural and Augmented Thermal Environments; Simultaneous Spectral Temporal Adaptive Raman Spectrometer - SSTARS; Improved Speed and Functionality of a 580-GHz Imaging Radar; Bolometric Device Based on Fluxoid Quantization; Algorithms for Learning Preferences for Sets of Objects; Model for Simulating a Spiral Software-Development Process; Algorithm That Synthesizes Other Algorithms for Hashing; Algorithms for High-Speed Noninvasive Eye-Tracking System; and Adapting ASPEN for Orbital Express.

Source record↗

NASA NTRS2014

Design of the VISITOR Tool: A Versatile ImpulSive Interplanetary Trajectory OptimizeR

The design of trajectories for interplanetary missions represents one of the most complex and important problems to solve during conceptual space mission design. To facilitate conceptual mission sizing activities, it is essential to obtain sufficiently accurate trajectories in a fast and repeatable manner. To this end, the VISITOR tool was developed. This tool modularly augments a patched conic MGA-1DSM model with a mass model, launch window analysis, and the ability to simulate more realistic arrival and departure operations. This was implemented in MATLAB, exploiting the built-in optimization tools and vector analysis routines. The chosen optimization strategy uses a grid search and pattern search, an iterative variable grid method. A genetic algorithm can be selectively used to improve search space pruning, at the cost of losing the repeatability of the results and increased computation time. The tool was validated against seven flown missions: the average total mission (Delta)V offset from the nominal trajectory was 9.1%, which was reduced to 7.3% when using the genetic algorithm at the cost of an increase in computation time by a factor 5.7. It was found that VISITOR was well-suited for the conceptual design of interplanetary trajectories, while also facilitating future improvements due to its modular structure.

Corpaccioli, Luca↗

DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗

NASA NTRS1991

Intelligent systems technology infrastructure for integrated systems

A system infrastructure must be properly designed and integrated from the conceptual development phase to accommodate evolutionary intelligent technologies. Several technology development activities were identified that may have application to rendezvous and capture systems. Optical correlators in conjunction with fuzzy logic control might be used for the identification, tracking, and capture of either cooperative or non-cooperative targets without the intensive computational requirements associated with vision processing. A hybrid digital/analog system was developed and tested with a robotic arm. An aircraft refueling application demonstration is planned within two years. Initially this demonstration will be ground based with a follow-on air based demonstration. System dependability measurement and modeling techniques are being developed for fault management applications. This involves usage of incremental solution/evaluation techniques and modularized systems to facilitate reuse and to take advantage of natural partitions in system models. Though not yet commercially available and currently subject to accuracy limitations, technology is being developed to perform optical matrix operations to enhance computational speed. Optical terrain recognition using camera image sequencing processed with optical correlators is being developed to determine position and velocity in support of lander guidance. The system is planned for testing in conjunction with Dryden Flight Research Facility. Advanced architecture technology is defining open architecture design constraints, test bed concepts (processors, multiple hardware/software and multi-dimensional user support, knowledge/tool sharing infrastructure), and software engineering interface issues.

Lum, Henry↗

DOE OSTI2024

Failure Criteria and Temperature Dependent Elastic Constants in the 3-D Elastic Orthotropic Model

Recent points of emphasis in the Library of Advanced Materials for Engineering (LAMÉ) have been to enable flexibility in formulations via the adoption of a variety of modular frameworks. While more established phenomenologies such as plasticity and viscoelasticity have been considered, elastically orthotropic models (e.g. elastic_3D_orthotropic) have not. For the elasticity component, not much can be modularized. However, a potential feature of interest would be the evaluation of failure criteria to consider the possibility of damage. Many such forms exist in the literature providing a good basis for modularity.

36 MATERIALS SCIENCE↗

NASA NTRS1998

Helioseismic Constraints on New Solar Models from the MoSEC Code

Evolutionary solar models are computed using a new stellar evolution code, MOSEC (Modular Stellar Evolution Code). This code has been designed with carefully controlled truncation errors in order to achieve a precision which reflects the increasingly accurate determination of solar interior structure by helioseismology. A series of models is constructed to investigate the effects of the choice of equation of state (OPAL or MHD-E, the latter being a version of the MHD equation of state recalculated by the author), the inclusion of helium and heavy-element settling and diffusion, and the inclusion of a simple model of mixing associated with the solar tachocline. The neutrino flux predictions are discussed, while the sound speed of the computed models is compared to that of the sun via the latest inversion of SOI-NMI p-mode frequency data. The comparison between models calculated with the OPAL and MHD-E equations of state is particularly interesting because the MHD-E equation of state includes relativistic effects for the electrons, whereas neither MHD nor OPAL do. This has a significant effect on the sound speed of the computed model, worsening the agreement with the solar sound speed. Using the OPAL equation of state and including the settling and diffusion of helium and heavy elements produces agreement in sound speed with the helioseismic results to within about +.-0.2%; the inclusion of mixing slightly improves the agreement.

Elliott, J. R.↗

DOE OSTI2017

MOOSE Framework Speed and Memory Optimizations

The Multiphysics Object Oriented Simulation Environment (MOOSE) framework has been developed to solve a variety of complex simulations ranging from groundwater flows to full reactor simulations. MOOSE excels at solving fully-implicit, fully-coupled, highly nonlinear models using the Jacobian Free Newton-Krylov (JFNK) method relying on years of expertise in several dependent packages including PETSc, libMesh, Hypre and many others. The modular design of MOOSE enables the rapid development of new physics models that can be coupled with relative ease within the framework for building up simulations of different levels of complexity. With the ongoing adoption of MOOSE to new application areas along with streamlining of existing simulations, the priorities must be adjusted to include code optimizations. This includes both execution speed and the memory footprint of MOOSE-based simulations. These two categories can be further broken down into ''micro-optimizations'' or source code optimizations and algorithmic optimizations where source code is restructured to accomplish the same tasks through a more efficient means. However, before any code optimizations can occur, one must have robust way of measuring these critical simulation properties to identify the best candidates for optimizations along with having a way to identify the effectiveness of proposed optimizations to the framework. This report discusses the preliminary work towards the implementation of a robust execution baseline of the framework and derivative applications under a variety of different simulations. In addition, several potential optimization target areas in both the MOOSE framework and dependent libraries have been identified. An implementation strategy and potential benefits are discussed.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Documentation, assessment, and improvements of fission gas modeling capabilities in BISON

Fission gas behavior critically affects nuclear fuel performance, influencing thermal conductivity, microstructure, swelling, and fuel-cladding interactions. The Simple Integrated Fission Gas Release and Swelling (Sifgrs) model, implemented within the BISON fuel performance code, provides advanced capabilities for modeling these phenomena. This manuscript reviews and assesses Sifgrs’ modular structure and submodels describing intragranular, intergranular, and release mechanisms. The modular implementation enables rapid improvements as our understanding advances and new fuel forms emerge. After an overview of capabilities, we present a comprehensive validation suite, comparing predictions to experimental data from tests under normal and transient conditions, including reproduction of the Vitanza curve. Results demonstrate Sifgrs’ accuracy, robustness, and applicability. Current limitations and ongoing efforts are discussed, including mechanistic, multiscale modeling, uncertainty quantification, and validation within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, supporting the safe and efficient use of nuclear fuels.

BISON↗

DOE OSTI2025

Flow instabilities in helical-coil steam generators for small modular reactors: A review

Here, this study covers the research and discoveries in two-phase flow-boiling instabilities available in the literature—specifically for a helical-coil steam generator (HCSG), including experimental findings, theoretical research, computational models, and system code analyses—supporting research and development of representative small modular reactors (SMRs). Like other new and advanced reactor systems, water-cooled SMRs require experimental data from both integral and separate thermal-hydraulics test facilities for the verification and validation (V&V) of the computational models and computer codes in order to design and obtain regulatory approval. The complex dynamics of two-phase flow-boiling instabilities includes flow regimes physics phenomena, flow-channel geometries, heat-transfer behavior, and interactions among the solid–liquid-gas within the system boundary, all of which are pivotal for understanding the design and operational challenges of SMRs. This study focuses on identifying the relevant knowledge gaps on boiling instabilities—specifically for a HCSG—and provides insights about future research direction optimizing the transport of thermal energy, mass-flow rates, and boundary conditions that ensure the adequate heat-transfer performance, operational stability, and safety associated with SMR systems.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1977

TVC actuator model

A prototype Space Shuttle Main Engine (SSME) Thrust Vector Control (TVC) Actuator analog model was successfully completed. The prototype, mounted on five printed circuit (PC) boards, was delivered to NASA, checked out and tested using a modular replacement technique on an analog computer. In all cases, the prototype model performed within the recording techniques of the analog computer which is well within the tolerances of the specifications.

Baslock, R. W.↗

DOE OSTI2021

A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem

Mobility on demand (MoD) systems show great promise in realizing flexible and efficient urban transportation. However, significant technical challenges arise from operational decision making associated with MoD vehicle dispatch and fleet rebalancing. For this reason, operators tend to employ simplified algorithms that have been demonstrated to work well in a particular setting. To help bridge the gap between novel and existing methods, we propose a modular framework for fleet rebalancing based on model-free reinforcement learning (RL) that can leverage an existing dispatch method to minimize system cost. In particular, by treating dispatch as part of the environment dynamics, a centralized agent can learn to intermittently direct the dispatcher to reposition free vehicles and mitigate against fleet imbalance. We formulate RL state and action spaces as distributions over a grid partitioning of the operating area, making the framework scalable and avoiding the complexities associated with multiagent RL. Numerical experiments, using real-world trip and network data, demonstrate that RL reduces waiting time by 28% to 38% for the same-day evaluation, 17% to 44% for cross-day evaluation, and 22% to 25% for cross-season evaluation compared with no rebalancing scenarios. This approach has several distinct advantages over baseline methods including: improved system cost; high degree of adaptability to the selected dispatch method; and the ability to perform scale-invariant transfer learning between problem instances with similar vehicle and request distributions.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1972

Systems simulation for an airport trailing vortex warning system

The approach, development, and limited system studies associated with a system simulation for an Airport Trailing Vortex Warning System are documented. The usefulness is shown of a systems engineering approach to the problem of developing a system, as dictated by aircraft vortices, which will increase air-traffic flow in the takeoff/landing corridors of busy airports while maintaining the required safety factor for each operation. The simulation program has been developed in a modular form which permits new, more sophisticated component models, when they become available and are required, to be incorporated into the program with a minimum of program modifications. This report documents a limited system study that has been performed using this Total System Simulation Model. The resulting preliminary system requirements, conclusions, and recommendations are given.

Jeffreys, H. B.↗

NASA NTRS1980

Advanced flight design systems subsystem performance models. Executive summary

Subsystem performance analysis required in flight design to assess the capability of the environmental control and life support system (ECLSS) to support the flight requirements and define operational procedures under contingency flight conditions is described. Current ECLSS modeling techniques are limited in the variety of configurations and they employ batch mode computer programs execution methods. Improvements in the variety of configurations that are modeled and a reduction in effort required for modeling and analysis is accomplished by developing a modular computer program which operates interactively.

Parker, K. C.↗

NASA NTRS1984

Manual of phosphoric acid fuel cell power plant optimization model and computer program

An optimized cost and performance model for a phosphoric acid fuel cell power plant system was derived and developed into a modular FORTRAN computer code. Cost, energy, mass, and electrochemical analyses were combined to develop a mathematical model for optimizing the steam to methane ratio in the reformer, hydrogen utilization in the PAFC plates per stack. The nonlinear programming code, COMPUTE, was used to solve this model, in which the method of mixed penalty function combined with Hooke and Jeeves pattern search was chosen to evaluate this specific optimization problem.

Lu, C. Y.↗

NASA NTRS1987

Computer Programs for Spacecraft Maneuvers

Multiple-encounter, multiple maneuver voyages analyzed in detail. Report describes ADAM (Advanced Analysis of Maneuvers) system, integrated collection of computer programs to aid design and analysis of maneuvers for deep space voyages involving multiple maneuvers and multiple encounters with planets and moons. Used in planning Galileo mission and used in both planning and operation of Voyager mission. Modularity of ADAM allows use of entirely new models, algorithms, trajectories, and maneuvering schedules. Characteristic great asset when spacecraft does not perform as planned.

Chadwick, Clyde↗