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An Overview of STS-132 MRM1 Cargo Element Thermal Model Development and Analyses
STS-132 was launched in May 2010 and delivered the Russian Mini Research Module 1 (MRM1) cargo element to the International Space Station as part of the ULF-4 assembly flight. The cargo element consisted of the module outfitted with externally mounted Multi-purpose Laboratory Module (MLM) Airlock, MLM radiator, Portable Work Platform (PWP), and a European Robotic Arm (ERA) spare elbow. Prior to every Shuttle flight, hardware developers are required to determine compatibility of their hardware to thermal environments experienced during the Shuttle mission and once the element is integrated with the ISS. Thermal models are provided to the Shuttle program to determine the impact of the payload on the Orbiter hardware, as well as the ISS program to determine impacts on other ISS payloads in the Orbiter. Historically the Russian International Partner (IP) develops models in formats not compatible with software used by Space Shuttle or ISS programs. This prompted NASA and Lockheed Martin to develop a unique set of thermal models for the MRM1 cargo element. Subsequent ULF-4 mission analyses performed with the models assessed the launch to activation response, identified operational criteria documented in flight rules, and ensured compliance with the mission timeline and no hazards to the crew, orbiter, or ISS. This presentation provides an overview of the work performed, depicts unique approaches in model development, discusses lessons learned, and issue resolution approaches. Though development and analysis efforts spanned over four years and presented various integration challenges it provided an example of successful collaboration with our International Partners.
Computational model development and validation of fuel dispersal phenomena
As the US nuclear industry is renewing efforts to extend the rod average burnup limits in existing pressurized water reactors, it becomes imperative to investigate the safety implications associated with high burnup fuel fragmentation and the potential dispersal of fragmented fuel into the reactor coolant system. Additionally, as there is a growing interest in transitioning to new nuclear fuel designs to accommodate higher fuel burnup levels, it becomes essential to conduct studies on fuel behavior during design basis accident scenarios, particularly during a postulated loss-of-coolant accident, in order to ensure the safe operation of light-water reactors. The present study develops a computational model to simulate the complex three-phase flow of the fuel dispersal phenomena that occur following a breach in the cladding, when the stream of solid fuel particles and carrier fission gas stream may interact with the surrounding liquid medium. Furthermore, the proposed framework considers the solid phase as discrete Lagrangian particles while the interpenetrating gas–liquid continuum is modeled using a Eulerian framework. The developed simulation framework is validated with experimental results performed in a separate-effect test facility by comparing predicted particle settlement locations with the experimental observations reported in the literature. Key highlights of this study include the interpretation of the high-pressure boundary conditions and the three-phase flow coupling strategy. Also discussed are the gas–liquid hydrodynamics and the behavior of particles as they are transported through the gas and liquid phases.
Update on metallic fuel performance model development
2019 Deliverable for Gen IV SFR Fuels group. Presentation summary of model development for metallic fuels in the BISON code.
Review of "ML for Surface Complexation Model Development"
The presentation given by Jadallah Zouabe on “ML for Surface Complexation Model Development”was extremely informative, but lacked some explanation of details that made the latter half hard to follow as someone outside of the field. He began his presentation with an anecdote to spilling milk or ink on the floor and seeing it spread, cleverly connecting that to the spread of contamination in the real world. He then explained the importance of being able to model contamination, as it allows specialists to see the potential effects on different areas and environments in the coming years. Heal so made it clear that the main issue trying to be addressed here is how expensive modelling is and that their goal is to make computationally cheaper models. The introduction was overall very well formulated and attention-grabbing, but it seemed to take up too much of the presentation time, as after this point the presentation lacked details and explanations.
Continuum Model Development for Flow and Transport in Electrochemical Systems
Stanford University (Subcontractor) shall provide the services of qualified multiscale modelers to perform tasks that contribute to reaching the objectives of the LDRD project entitled Automated and Accelerated Continuum Model Development for Electrochemical Systems (Tracking number 24-ERD-051). These tasks relate to the development, deployment, and validation of multiscale models relevant to flow and transport in electrochemical systems.
A numerical study of thunderstorm electrification - Model development and case study
A numerical model was developed for examining the thunderstorm electrification process in which it is assumed that the electrification is entirely due to noninductive charge transfer between colliding ice crystals and hail. Since this ice-hail charge mechanism is very dependent on particle sizes and distributions, an explicit microphysical framework is used. To maintain simplicity, the electrification model is kinematic; thus the temperature and velocity fields are input into the electrification model. The cloud model of Taylor (1989) was used to generate the temperature and velocity fields to examine the July 19, 1981, Cooperative Convective Precipitation Experiment thundercloud. Using these fields, the electrification model produced time-dependent ice particle concentrations, radar reflectivities, charge, and vertical electric field distributions in good general agreement with those observed. The model produced a maximum electric field strength of 1.27 kV/cm, which is on the order of that needed for lightning initiation, and this maximum occurred very close to the time of the observed discharge. Thus, the ice-hail charge mechanism appears to have played an important role in the electrical development of the July 19 cloud.
Shuttle Spacesuit (Radiation) Model Development
A detailed spacesuit computational model is being developed at the Langley Research Center for exposure evaluation studies. The details of the construction of the spacesuit are critical to an estimate of exposures and for assessing the health risk to the astronaut during extravehicular activity (EVA). Fine detail of the basic fabric structure, helmet, and backpack is required to assure a valid evaluation. The exposure fields within the Computerized Anatomical Male (CAM) and Female (CAF) are evaluated at 148 and 156 points, respectively, to determine the dose fluctuations within critical organs. Exposure evaluations for ambient environments will be given and potential implications for geomagnetic storm conditions discussed.
Probabilistic Model Development
Objective: Develop a Probabilistic Model for the Solar Energetic Particle Environment. Develop a tool to provide a reference solar particle radiation environment that: 1) Will not be exceeded at a user-specified confidence level; 2) Will provide reference environments for: a) Peak flux; b) Event-integrated fluence; and c) Mission-integrated fluence. The reference environments will consist of: a) Elemental energy spectra; b) For protons, helium and heavier ions.
High speed turboprop aeroacoustic study (counterrotation). Volume 1: Model development
The isolated counterrotating high speed turboprop noise prediction program was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in NASA-Lewis' 8x6 and 9x15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counterotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attach was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combines into a single prediction program, results of which were compared with data taken during the flight test of the B727/UDF engine demonstrator aircraft. Satisfactory comparisons between prediction and measured data for the demonstrator airplane, together with the identification of a nontraditional radiation mechanism for propellers at angle of attack are achieved.
Continuum Model Development for Electrochemical Systems (Statement of Work: Ilenia Battiato Subcontract)
The subcontractor shall provide the services of qualified multiscale modelers to perform tasks that contribute to reaching the objectives of the LDRD project entitled Automated and Accelerated Continuum Model Development for Electrochemical Systems (Tracking number 24-ERD-051). These tasks relate to the development, deployment, and validation of multiscale models relevant to electrochemical systems.
Data Driven Model Development for the Supersonic Semispan Transport (S(sup 4)T)
We investigate two common approaches to model development for robust control synthesis in the aerospace community; namely, reduced order aeroservoelastic modelling based on structural finite-element and computational fluid dynamics based aerodynamic models and a data-driven system identification procedure. It is shown via analysis of experimental Super- Sonic SemiSpan Transport (S4T) wind-tunnel data using a system identification approach it is possible to estimate a model at a fixed Mach, which is parsimonious and robust across varying dynamic pressures.
Workshop Report: Rural Electric Cooperative Distributed Energy Resource Business Model Development Workshops
The United States' energy future is being shaped by decades of technology innovation, rapidly changing consumer requirements, and governmental focus on securing reliable, low-cost energy sources. With expanded electrification and increased emphasis on grid reliability coupled with the heightened complexity and risks associated with transmission infrastructure, the use of distributed energy resources (DERs) is more commonly being considered a safe, efficient, and cost-effective way to maintain grid resilience and reliability. Amidst improvements in performance, decreasing costs, and unprecedented federal policy support for DERs, electric cooperatives are considering new opportunities to use these assets to ensure secure and reliable operations for millions of customers. In light of these developments, a series of workshops were held to collaborate on the development of business models for DERs in rural electric cooperative ecosystems. The first workshop was held July 11, 2024, at the Tri-State Generation and Transmission Association Inc. headquarters in Westminster, Colorado (hereafter referred to as the "Tri-State Workshop"). The second workshop was hosted by PNGC Power on Oct. 9, 2024, in Portland, Oregon (hereafter referred to as the "PNGC Power Workshop"). These workshops convened representatives from G&Ts, distribution cooperatives,2 the energy industry, the financial community, the U.S. government, national and regional organizations, and national laboratories to share perspectives on the unique needs, challenges, and opportunities that they face as DERs are further integrated into the grid. The workshops were designed to address the following objectives: (1) develop the enabling attributes of electric cooperative DER business models, (2) explore pathways for generating community benefits from these assets, and (3) identify technical challenges and market risks for DERs in rural electric cooperative service territories. This report outlines key findings and major themes identified by workshop participants that federal agencies, G&Ts, distribution cooperatives, and other entities can consider to advance electric cooperative DER business models.
Frankenstein’s ROMster: Avoiding pitfalls of reduced-order model development
Reduced-order models (ROMs) are a widely used and powerful approach to reducing the complexity of predictive physics-based numerical simulations for a wide range of applications, including electronics and fluid mechanics such as geologic CO 2 sequestration (GCS). ROMs are critical for optimization, sensitivity analysis, model calibration and uncertainty quantification where full-order models cannot be feasibly executed many times. Traditional approaches generate a single ROM for each simulated response (e.g., CO 2 injection rates, pH changes) based on a set of training simulations. Here, we demonstrate that a single ROM can display excellent overall predictive statistics, but have predictions that dramatically and unacceptably deviate from simulator responses especially when the response variable has a large range (i.e., vary over multiple orders of magnitude). For example, we show that a traditional statistically-high-performing GCS ROM (coefficient of determination R 2 of 0.99) can have average absolute relative errors of over 200%. To address this, we propose a new and novel approach where a set of sub-ROMs are generated to overcome the potential pitfalls in traditional single ROM development. The effectiveness of the proposed approach—the ROMster framework—is demonstrated using a case study of predicted CO 2 injection rates for GCS. We find our approach is a robust and general framework for ROM development, reducing the average “error” from 200% to only 4% in our case study.
A Unified Ice Microphysical Parameterization for Numerical Models: Development and Testing with In-situ Data
The primary goal of the project is to develop and test new microphysical parameterizations of ice crystal growth. Over the past 7 years, we have developed a bulk ice microphysical model that evolves a measure of particle shape and density during vapor diffusional growth. The method allows smaller, pristine ice crystals to evolve into larger snow crystals in a more natural fashion than traditional microphysical schemes. In doing so, the new method avoids problems that occur when ice is transferred among pre-defined classes. The new model was developed and tested for vapor grown ice only, and so the goal of this project is to develop bulk parameterizations of the missing physics for the model including the prediction of surface deposition coefficients, riming, and aggregation. The parameterizations are being developed using prior laboratory data as a constraint, and then will be tested in simulations of case studies.
Research in Integrated Assessment Inter-Model Development, Testing and Diagnostics (Final Technical Report)
This is the final report on the second phase (spanning 2013-2018) of a project focused on further establishing an integrated assessment modeling (IAM) community research program on IAM model development, diagnostic testing, and inter-comparisons (PIAMDDI), including multi-model scenario ensemble analyses. The program was dedicated to improving the science of integrated assessment by doing cutting edge research in critical scientific areas of IAM development, and integrating that research with research programs on improved methods for model diagnostics, inter-comparison and ensemble-like analyses. We continued to link this program closely to other climate change research programs in the U.S. and abroad, and to make the work highly transparent, accessible and credible. As anticipated, progress in the scientific research areas informed the model comparison methods development and scenario tasks, and the comparisons and ensemble activities helped set priorities for the research areas.
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.
The Challenge of Grounding Planning in Simulation with an Interactive Model Development Environment
A principal obstacle to fielding automated planning systems is the difficulty of modeling. Physical systems are modeled conventionally based on specification documents and the modeler's understanding of the system. Thus, the model is developed in a way that is disconnected from the system's actual behavior and is vulnerable to manual error. Another obstacle to fielding planners is testing and validation. For a space mission, generated plans must be validated often by translating them into command sequences that are run in a simulation testbed. Testing in this way is complex and onerous because of the large number of possible plans and states of the spacecraft. Though, if used as a source of domain knowledge, the simulator can ease validation. This paper poses a challenge: to ground planning models in the system physics represented by simulation. A proposed, interactive model development environment illustrates the integration of planning and simulation to meet the challenge. This integration reveals research paths for automated model construction and validation.