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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Isothermal evaporation process simulation using the Pitzer model for the Quinary system LiCl–NaCl–KCl–SrCl 2 –H 2 O at 298.15 K

In this study, the Pitzer thermodynamic model for solid-liquid equilibria in the quinary system LiCl–NaCl–KCl–SrCl 2 –H 2 O at 298.15 K was constructed by selecting the proper parameters for the subsystems in the literature. The solubility data of the systems NaCl–SrCl 2 –H 2 O, KCl–SrCl 2 –H 2 O, LiCl–SrCl 2 –H 2 O, and NaCl–KCl–SrCl 2 –H 2 O were used to evaluate the model. Good agreement between the experimental and calculated solubilities shows that the model is reliable. The Pitzer model for the quinary system at 298.15 K was then used to calculate the component solubilities and conduct computer simulation of isothermal evaporation of the mother liquor for the oilfield brine from Nanyishan district in the Qaidam Basin. The evaporation-crystallization path and sequence of salt precipitation, change in concentration and precipitation of lithium, sodium, potassium, and strontium, and water activities during the evaporation process were demonstrated. The salts precipitated from the brine in the order : KCl, NaCl, SrCl 2 ∙6H 2 O, SrCl 2 ∙2H 2 O, and LiCl∙H 2 O. The entire evaporation process may be divided into six stages. In each stage the variation trends for the relationships between ion concentrations or water activities and the evaporation ratio are different. This result of the simulation of brines can be used as a theoretical reference for comprehensive exploitation and utilization of this type of brine resources.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-F-T-94: Plan2pdf - a Software Tool for Automatic Plan Report for Philips Pinnacle TPS

Purpose: To implement an automatic electronic PDF plan reporting tool for Philips Pinnacle treatment planning system (TPS) Methods: An electronic treatment plan reporting software is developed by us to enable fully automatic PDF report from Pinnacle TPS to external EMR programs such as MOSAIQ. The tool is named “plan2pdf”. plan2pdf is implemented using Pinnacle scripts, Java and UNIX shell scripts, without any external program needed. plan2pdf supports full auto-mode and manual mode reporting. In full auto-mode, with a single mouse click, plan2pdf will generate a detailed Pinnacle plan report in PDF format, which includes customizable cover page, Pinnacle plan summary, orthogonal views through each plan POI and maximum dose point, DRR for each beam, serial transverse views captured throughout the dose grid at a user specified interval, DVH and scorecard windows. The final PDF report is also automatically bookmarked for each section above for convenient plan review. The final PDF report can either be saved on a user specified folder on Pinnacle, or it can be automatically exported to an EMR import folder via a user configured FTP service. In manual capture mode, plan2pdf allows users to capture any Pinnacle plan by full screen, individual window or rectangular ROI drawn on screen. Furthermore, to avoid possible patients’ plan mix-up during auto-mode reporting, a user conflict check feature is included in plan2pdf: it prompts user to wait if another patient is being exported by plan2pdf by another user. Results: plan2pdf is tested extensively and successfully at our institution consists of 5 centers, 15 dosimetrists and 10 physicists, running Pinnacle version 9.10 on Enterprise servers. Conclusion: plan2pdf provides a highly efficient, user friendly and clinical proven platform for all Philips Pinnacle users, to generate a detailed plan report in PDF format for external EMR systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

High-throughput phase-field simulations and machine learning of resistive switching in resistive random-access memory

Metal oxide-based Resistive Random-Access Memory (RRAM) exhibits multiple resistance states, arising from the activation/deactivation of a conductive filament (CF) inside a switching layer. Understanding CF formation kinetics is critical to achieving optimal functionality of RRAM. Here a phase-field model is developed, based on materials properties determined by ab initio calculations, to investigate the role of electrical bias, heat transport and defect-induced Vegard strain in the resistive switching behavior, using MO 2- x systems such as HfO 2- x as a prototypical model system. It successfully captures the CF formation and resultant bipolar resistive switching characteristics. High-throughput simulations are performed for RRAMs with different material parameters to establish a dataset, based on which a compressed-sensing machine learning is conducted to derive interpretable analytical models for device performance (current on/off ratio and switching time) metrics in terms of key material parameters (electrical and thermal conductivities, Vegard strain coefficients). These analytical models reveal that optimal performance (i.e., high current on/off ratio and low switching time) can be achieved in materials with a low Lorenz number, a fundamental material constant. This work provides a fundamental understanding to the resistive switching in RRAM and demonstrates a computational data-driven methodology of materials selection for improved RRAM performance, which can also be applied to other electro-thermo-mechanical systems.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Planning for the semiconductor manufacturer of the future

Texas Instruments (TI) is currently contracted by the Air Force Wright Laboratory and the Defense Advanced Research Projects Agency (DARPA) to develop the next generation flexible semiconductor wafer fabrication system called Microelectronics Manufacturing Science & Technology (MMST). Several revolutionary concepts are being pioneered on MMST, including the following: new single-wafer rapid thermal processes, in-situ sensors, cluster equipment, and advanced Computer Integrated Manufacturing (CIM) software. The objective of the project is to develop a manufacturing system capable of achieving an order of magnitude improvement in almost all aspects of wafer fabrication. TI was awarded the contract in Oct., 1988, and will complete development with a fabrication facility demonstration in April, 1993. An important part of MMST is development of the CIM environment responsible for coordinating all parts of the system. The CIM architecture being developed is based on a distributed object oriented framework made of several cooperating subsystems. The software subsystems include the following: process control for dynamic control of factory processes; modular processing system for controlling the processing equipment; generic equipment model which provides an interface between processing equipment and the rest of the factory; specification system which maintains factory documents and product specifications; simulator for modelling the factory for analysis purposes; scheduler for scheduling work on the factory floor; and the planner for planning and monitoring of orders within the factory. This paper first outlines the division of responsibility between the planner, scheduler, and simulator subsystems. It then describes the approach to incremental planning and the way in which uncertainty is modelled within the plan representation. Finally, current status and initial results are described.

Fargher, Hugh E.↗
DOE OSTI2021

Computationally Tractable High-Fidelity Representation of Global Hydrology in ESMs via Machine Learning Approaches to Scale-Bridging

Focal Areas: This paper responds primarily to Focal Area 2, focusing on AI techniques to improve model fidelity. Science Challenge: “Hyperresolution” [1, 2] land surface models (LSMs) running at far higher resolution than typically employed in global Earth system models (ESMs) can help answer critical questions about the water cycle and associated ecosystem and biogeochemical feedbacks. Even with all foreseeable advances in computing power and efficient solver algorithms, however, employing hyperresolution LSMs inside ESMs for studies of long-term global climate is not computationally feasible. Instead, we argue for incorporating the fidelity of hyperresolution LSMs only where and when it is needed by using machine learning approaches to scale-bridging.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

Oliker, Leonid↗
NASA NTRS1993

Feasibility study of an orbiting laboratory for testing CSI technology

A concept for an orbiting laboratory for testing Controls-Structures Integration (CSI) technology is described. The CSI-Star concept reflects a lower cost, higher risk approach. The concept supports demonstration and validation testing for critical CSI technologies at a cost of $20M to $26M with a 1-year reliability of approximately 0.9. The Ball Aerospace QuickStar bus is the carrier for the CSI test article. QuickStar is launched as a secondary payload on the McDonnell Douglas Delta 2. The QuickStar/Delta 2 approach is flight proven. The CSI test article is a 20 foot, 1 Hz, truss beam which is deployed from the QuickStar bus. The test article is well instrumented for quality system identification. The laboratory provides three layers of active control consisting of global vibration suppression along the truss beam, vibration isolation between the beam and instrument platforms, and vibration compensation through the use of gimbaled platforms which point lasers relative to optical sensor targets. The configuration simulates the dynamics of multi-instrument science platforms such as those of the Earth Observation System (EOS) while maintaining strong ties to astrophysics missions such as the Optical Interferometer. Uplink/downlink services and a reprogrammable computer provide flexibility for long-term investigations by members of the CSI community (NASA, DoD, academia, and industry). CSI-Star fills the gap between short-term experiments, which have been conducted primarily on the Shuttle, and future science missions which require the technology. The on-orbit maturity of CSI technology must be established to obtain acceptance by project managers and to promote injection of the technology into future science missions.

Bicos, Andrew S.↗
DOE OSTI2024

A Four-Layer Cyber-Physical Security Model for Electric Machine Drives Considering Control Information Flow

Despite the IEEE Power Electronics Society (PELS) establishing Technical Committee 10 on Design Methodologies with a focus on the cyber-physical security of power electronics systems, a holistic design methodology for addressing security vulnerabilities remains underdeveloped. This gap largely stems from the limited integration of computer science and power/control engineering studies in this interdisciplinary field. Addressing the inadequacy of unilateral cyber or control perspectives, this article presents a novel four-layer cyber-physical security model specifically designed for electric machine drives. Central to this model is the innovative control information flow (CIF) model, residing within the control layer, which serves as a pivotal link between the cyber layer's vulnerable resources and the physical layer's state-space models. By mapping vulnerable resources to control variable space and tracing attack propagation, the CIF model facilitates accurate impact predictions based on tainted control laws. The effectiveness and validity of this proposed model are demonstrated through hardware experiments involving two typical cyber-attack scenarios, underscoring its potential as a comprehensive framework for multidisciplinary security strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Intelligent Information Fusion in the Aviation Domain: A Semantic-Web based Approach

Information fusion from multiple sources is a critical requirement for System Wide Information Management in the National Airspace (NAS). NASA and the FAA envision creating an "integrated pool" of information originally coming from different sources, which users, intelligent agents and NAS decision support tools can tap into. In this paper we present the results of our initial investigations into the requirements and prototype development of such an integrated information pool for the NAS. We have attempted to ascertain key requirements for such an integrated pool based on a survey of DSS tools that will benefit from this integrated pool. We then advocate key technologies from computer science research areas such as the semantic web, information integration, and intelligent agents that we believe are well suited to achieving the envisioned system wide information management capabilities.

Ashish, Naveen↗
DOE OSTI2019

In Situ Visualization for Computational Science

In situ visualization, i.e., visualizing simulation data as it is generated, is an emerging processing paradigm in response to trends in the area of high-performance computing. This paradigm holds great promise in its ability to access increased spatio-temporal resolution and leverage extensive computational power. However, the paradigm is also widely viewed as limiting when it comes to exploration-oriented use cases and further will require visualization systems to become more and more complicated and constrained. Additionally, there are many open research topics within situ visualization. The Dagstuhl seminar 18271 "In Situ Visualization for Computational Science" brought together researchers and practitioners from three communities (computational science, high-performance computing, and scientific visualization) to share interesting findings, to identify lines of open research, and to determine a medium-term research agenda that addresses the most pressing problems. This report summarizes the outcomes and findings of the seminar.

Computational Science↗
DOE OSTI2015

TU-G-BRD-02: Automated Systematic Quality Assurance Program for Radiation Oncology Information System Upgrades

Purpose: To: (1) describe an independent, automated, systematic software-based protocol for verifying clinical data accuracy/integrity for mitigation of data corruption/loss risks following radiation oncology information system (ROIS) upgrades; and (2) report on application of this approach in an academic/community practice environment. Methods: We propose a robust approach to perform quality assurance on the ROIS after an upgrade, targeting four data sources: (1) ROIS relational database; (2) ROIS DICOM interface; (3) ROIS treatment machine data configuration; and (4) ROIS-generated clinical reports. We investigated the database schema for differences between pre-/post-upgrade states. Paired DICOM data streams for the same object (such as RT-Plan/Treatment Record) were compared between pre-/post-upgrade states for data corruption. We examined machine configuration and related commissioning data files for changes and corruption. ROIS-generated treatment appointment and treatment parameter reports were compared to ensure patient encounter and treatment plan accuracy. This protocol was supplemented by an end-to-end clinical workflow test to verify essential ROI functionality and integrity of components interfaced during patient care chain of activities. We describe the implementation of this protocol during a Varian ARIA system upgrade at our clinic. Results: We verified 1,638 data tables with 2.4 billion data records. For 222 under-treatment patients, 605 DICOM RT plans and 13,480 DICOM treatment records retrieved from the ROIS DICOM interface were compared, with no differences in fractions, doses delivered, or treatment parameters. We identified 82 new data tables and 78 amended/deleted tables consistent with the upgrade. Reports for 5,073 patient encounters over a 2-week horizon were compared and were identical to those before the upgrade. Content in 12,237 xml machine files was compared, with no differences identified. Conclusion: An independent QA/validation approach for ROIS upgrades was developed and implemented at our clinic. The success of this approach ensures a robust QA of ROIS upgrades without manual paper/electronic checks and associated intensive labor.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1987

Focus of attention in systems for visual monitoring of experiments

The problem of designing a computerized experiment monitoring system for use in a space station or elsewhere is examined. It is shown that the essential challenge of such a system - attaining a reasonable expected running time - can be attacked using the concept of focus of attention and by exploiting parallelism. The use of the Contract Net Protocol for the latter purpose is discussed. The use of ideas from information science to help focus a programs's efforts on those computations likely to bring results is addressed, and the incorporation of those ideas into a design in order to aid the system in deciding upon the best course of action is considered.

Blank, G. E.↗
DOE OSTI2016

Using quantum chemistry muscle to flex massive systems: How to respond to something perturbing

Computational chemistry uses the theoretical advances of quantum mechanics and the algorithmic and hardware advances of computer science to give insight into chemical problems. It is currently possible to do highly accurate quantum chemistry calculations, but the most accurate methods are very computationally expensive. Thus it is only feasible to do highly accurate calculations on small molecules, since typically more computationally efficient methods are also less accurate. The overall goal of my dissertation work has been to try to decrease the computational expense of calculations without decreasing the accuracy. In particular, my dissertation work focuses on fragmentation methods, intermolecular interactions methods, analytic gradients, and taking advantage of new hardware.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement

The standard LU factorization-based solution process for linear systems can be enhanced in speed or accuracy by employing mixed-precision iterative refinement. Most recent work has focused on dense systems. We investigate the potential of mixed-precision iterative refinement to enhance methods for sparse systems based on approximate sparse factorizations. In doing so, we first develop a new error analysis for LU- and GMRES-based iterative refinement under a general model of LU factorization that accounts for the approximation methods typically used by modern sparse solvers, such as low-rank approximations or relaxed pivoting strategies. We then provide a detailed performance analysis of both the execution time and memory consumption of different algorithms, based on a selected set of iterative refinement variants and approximate sparse factorizations. Our performance study uses the multifrontal solver MUMPS, which can exploit block low-rank factorization and static pivoting. We evaluate the performance of the algorithms on large, sparse problems coming from a variety of real-life and industrial applications showing that mixed-precision iterative refinement combined with approximate sparse factorization can lead to considerable reductions of both the time and memory consumption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Plasma Facing Components with Capillary Porous System and Liquid Metal Coolant Flow

Liquid metal can create a renewable protective surface on plasma facing components (PFC), with an additional advantage of deuterium pumping and the prospect of tritium extraction if liquid lithium (LL) is used and maintained below 450 C, the temperature above which LL vapor pressure begins to contaminate the plasma. LM can also be utilized as an efficient coolant, driven by the Lorentz force created with the help of the magnetic field in fusion devices. Capillary porous systems can serve as a conduit of LM and simultaneously provide stabilization of the LM flow, protecting against spills into the plasma. Recently a combination of a fast-flowing LM cooling system with a porous plasma facing wall (CPSF) was investigated [Khodak and Maingi (2021)]. The system takes an advantage of a magnetohydrodynamics velocity profile, as well as attractive LM properties to promote efficient heat transfer from the plasma to the LL at low pumping energy cost, relative to the incident heat flux on the PFC. In case of a disruption leading to excessive heat flux from the plasma to the LM PFCs, LL evaporation can stabilize the PFC surface temperature, due to high evaporation heat and apparent vapor shielding. The proposed CPSF was optimized analytically for the conditions of a Fusion Nuclear Science Facility [Kessel et al. (2019)]: 10T toroidal field and 10 MW/m2 peak incident heat flux. Computational fluid dynamics analysis confirmed that a CPSF system with 2.5 mm square channels can pump enough LL so that no additional coolant is needed.

High Heat Flux↗
DOE OSTI2017

Sepsis reconsidered: Identifying novel metrics for behavioral landscape characterization with a high-performance computing implementation of an agent-based model

Objectives: Sepsis affects nearly 1 million people in the United States per year, has a mortality rate of 28–50% and requires more than $20 billion a year in hospital costs. Over a quarter century of research has not yielded a single reliable diagnostic test or a directed therapeutic agent for sepsis. Central to this insufficiency is the fact that sepsis remains a clinical/physiological diagnosis representing a multitude of molecularly heterogeneous pathological trajectories. Advances in computational capabilities offered by High Peformance Computing (HPC) platforms call for an evolution in the investigation of sepsis to attempt to define the boundaries of traditional research (bench, clinical and computational) through the use of computational proxy models. We present a novel investigatory and analytical approach, derived from how HPC resources and simulation are used in the physical sciences, to identify the epistemic boundary con- ditions of the study of clinical sepsis via the use of a proxy agent-based model of systemic inflammation. Design: Current predictive models for sepsis use correlative methods that are limited by patient heterogeneity and data sparseness. We address this issue by using an HPC version of a system-level validated agent-based model of sepsis, the Innate Immune Response ABM (IIRBM), as a proxy system in order to identify boundary conditions for the possible behavioral space for sepsis. We then apply advanced analysis derived from the study of Random Dynamical Systems (RDS) to identify novel means for characterizing system behavior and providing insight into the tractability of traditional investigatory methods. Results: The behavior space of the IIRABM was examined by simulating over 70 million sepsis patients for up to 90 days in a sweep across the following parameters: cardio-respiratory-metabolic resilience; microbial invasiveness; microbial toxigenesis; and degree of nosocomial exposure. In addition to using established methods for describing parameter space, we developed two novel methods for characterizing the behavior of a RDS: Probabilistic Basins of Attraction (PBoA) and Stochastic Trajectory Analysis (STA). Computationally generated behavioral landscapes demonstrated attractor structures around stochastic re- gions of behavior that could be described in a complementary fashion through use of PBoA and STA. The stochasticity of the boundaries of the attractors highlights the challenge for correlative attempts to characterize and classify clinical sepsis. Conclusions: HPC simulations of models like the IIRABM can be used to generate approximations of the behavior space of sepsis to both establish “boundaries of futility” with respect to existing investi- gatory approaches and apply system engineering principles to investigate the general dynamic properties of sepsis to provide a pathway for developing control strategies. Here, the issues that bedevil the study and treatment of sepsis, namely clinical data sparseness and inadequate experimental sampling of system behavior space, are fundamental to nearly all biomedical research, manifesting in the “Crisis of Reproducibility” at all levels. HPC-augmented simulation-based research offers an investigatory strategy more consistent with that seen in the physical sciences (which combine experiment, theory and simulation), and an opportunity to utilize the leading advances in HPC, namely deep machine learning and evolutionary computing, to form the basis of an iterative scientific process to meet the full promise of Precision Medicine (right drug, right patient, right time).

59 BASIC BIOLOGICAL SCIENCES↗