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DOE OSTI2025

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗

DOE OSTI2024

MULTI-LEADER: MULTI-source LEarning-Accelerated Design of high-Efficiency multi-stage compRessor (Final Technical Report)

The objective of MULTI-LEADER is to cut design costs by 80% while generating more energy-efficient designs of multi-stage compressors by developing and implementing novel machine learning (ML) techniques, which enable faster and fewer design iterations, improved solver performance, and concurrent multi-disciplinary design. Current industrial practices for the design of multi-stage compressors involve simulation-based design optimization with successive levels of model fidelity, iteratively evaluated between distinct disciplines, one stage at a time to tackle the high dimensional design variations. This project addresses these key design challenges: (1) concurrent optimization of multiple stages under many non-linear constraints; (2) multitude of evaluation of high-fidelity and expensive solvers and their gradients during optimization convergence in high-dimensional design; (3) multi-disciplinary design to maximize aerodynamic performance while guaranteeing structural integrity and additive manufacturability; (4) utilization of multiple fidelity of solvers with disparate parameterization and modeling assumptions. MULTI-LEADER achieved more than 5x speed up in detailed design of more energy-efficient compressors via these machine learning (ML) innovations: (i) rapid design surrogates by multi-source learning from diverse fidelities across multiple disciplines, (ii) physics-constrained data-augmented modeling for improved empiricism, (iii) generative manifold embedding for high dimensional concurrent design without gradient information; (iv) budget-constrained fidelity-adaptive sampling towards fewer design iterations.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1992

Thermostructural tailoring of fiber composite structures

A significant area of interest in design of complex structures involves the study of multidisciplined problems. The coordination of several different intricate areas of study to obtain a particular design of a structure is a new and pressing area of research. In the past, each discipline would perform its task consecutively using the appropriate inputs from the other disciplines. This process usually required several time-consuming iterations to obtain a satisfactory design. The alternative pursued here is combining various participating disciplines and specified design requirements into a formal structural computer code. The main focus of this research is to develop a multidiscipline structural tailoring method for select composite structures and to demonstrate its application to specific areas. The development of an integrated computer program involves the coupling of three independent computer programs using an excutive module. This module will be the foundation for integrating a structural optimizer, a composites analyzer and a thermal analyzer. With the completion of the executive module, the first step was taken toward the evolution of multidiscipline software in the field of composite mechanics. Through the use of an array of cases involving a variety of objective functions/constraints and thermal-mechanical load conditions, it became evident that simple composite structures can be designed to a combined loads environment.

Acquaviva, Thomas H.↗

NASA NTRS1997

A Human Factors Analysis of EVA Time Requirements

Human Factors Engineering (HFE) is a discipline whose goal is to engineer a safer, more efficient interface between humans and machines. HFE makes use of a wide range of tools and techniques to fulfill this goal. One of these tools is known as motion and time study, a technique used to develop time standards for given tasks. During the summer of 1995, a human factors motion and time study was initiated with the goals of developing a database of EVA task times and developing a method of utilizing the database to predict how long an EVA should take. Initial development relied on the EVA activities performed during the STS-61 (Hubble) mission. The first step of the study was to become familiar with EVA's, the previous task-time studies, and documents produced on EVA's. After reviewing these documents, an initial set of task primitives and task-time modifiers was developed. Data was collected from videotaped footage of two entire STS-61 EVA missions and portions of several others, each with two EVA astronauts. Feedback from the analysis of the data was used to further refine the primitives and modifiers used. The project was continued during the summer of 1996, during which data on human errors was also collected and analyzed. Additional data from the STS-71 mission was also collected. Analysis of variance techniques for categorical data was used to determine which factors may affect the primitive times and how much of an effect they have. Probability distributions for the various task were also generated. Further analysis of the modifiers and interactions is planned.

Pate, Dennis W.↗

DOE OSTI2025

An investigation on machine learning predictive accuracy improvement and uncertainty reduction using VAE-based data augmentation

The confluence of ultrafast computers with large memory, rapid progress in Machine Learning (ML) algorithms, and the availability of large datasets place multiple engineering fields at the threshold of dramatic progress. However, a unique challenge in nuclear engineering is data scarcity because experimentation on nuclear systems is usually more expensive and time-consuming than most other disciplines. One potential way to resolve the data scarcity issue is deep generative learning, which uses certain ML models to learn the underlying distribution of existing data and generate synthetic samples that resemble the real data. In this way, one can significantly expand the dataset to train more accurate predictive ML models. In this study, our objective is to evaluate the effectiveness of data augmentation using variational autoencoder (VAE)-based deep generative models. We investigated whether the data augmentation leads to improved accuracy in the predictions of a deep neural network (DNN) model trained using the augmented data. Additionally, the DNN prediction uncertainties are quantified using Bayesian Neural Networks (BNN) and conformal prediction (CP) to assess the impact on predictive uncertainty reduction. To test the proposed methodology, we used TRACE simulations of steady-state void fraction data based on the NUPEC Boiling Water Reactor Full-size Fine-mesh Bundle Test (BFBT) benchmark. Here, we found that augmenting the training dataset using VAEs has improved the DNN model’s predictive accuracy, improved the prediction confidence intervals, and reduced the prediction uncertainties.

Bayesian neural network↗

DOE OSTI2023

A high-throughput and low-waste viability assay for microbes

Abstract Counting viable cells is a universal practice in microbiology. The colony-forming unit (CFU) assay has remained the gold standard to measure viability across disciplines, but it is time-intensive and resource-consuming. Here we describe the geometric viability assay (GVA) that replicates CFU measurements over 6 orders of magnitude while reducing over 10-fold the time and consumables required. GVA computes a sample’s viable cell count on the basis of the distribution of embedded colonies growing inside a pipette tip. GVA is compatible with Gram-positive and Gram-negative planktonic bacteria ( Escherichia coli, Pseudomonas aeruginosa and Bacillus subtilis ), biofilms and fungi ( Saccharomyces cerevisiae ). Laborious CFU experiments such as checkerboard assays, treatment time-courses and drug screens against slow-growing cells are simplified by GVA. The ease and low cost of GVA evinces that it can replace existing viability assays and enable viability measurements at previously impractical scales.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2005

Instrumentation and Measurements for Electron Emission from Charged Insulators

The electron was first discovered in 1898 by Sir John Joseph Thomson and has since been the subject of detailed study by nearly every scientific discipline. At nearly the same time Heinrich Rudolf Hertz conducted a series of experiments using cathode tubes, high potentials and ultraviolet light. When applying a large potential to a cathode he found that an arching event across the metal plates would occur. In addition, when shining an ultraviolet light on the metal he found that less potential was required to induce the spark. This result, taken together with other electrical phenomena brought about by the shining of light upon metal and was eventually termed the photoelectric effect. The work of Thomson and Hertz represent the beginning of electron emission studies and a body of ideas that pervade nearly all aspects of physics. In particular these ideas tell us a great deal about the nature of physical interactions within solids. In this thesis we will focus on the emission of electrons induced by an incident electron source over a range of energies, in which one can observe changes in emitted electron flux and energy distribution. In particular, when energetic particles impinge on a solid they can impart their energy, exciting electrons within the material. If this energy is sufficient to overcome surface energy barriers such as the work function, electron affinity or surface charge potential, electrons can escape from the material. The extent of electron emission from the material can be quantified as the ratio of incident particle flux to emitted particle flux, and is termed the electron yield.

Sim, Alec M.↗

NASA NTRS2016

Toward a New Generation of Agricultural System Data, Models, and Knowledge Products: State of Agricultural Systems Science

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

Livestock models↗

NASA NTRSDate not supplied

A Gaussian Process Enhancement to Linear Parameter Varying Models

Simulation and analysis for modern engineering systems now routinely requires the merging of multiple disciplines, physical-domains, time-scales, and data sets — all at ever increasing levels. These capabilities are especially needed in the domain of Advanced Air Mobility, where rapidly emerging vehicle designs are significantly more complex, while having to be both cost-effective and safe. To meet these engineering challenges, machine learning methods are an attractive option for merging models and data across multiple areas while providing uncertainty quantification and maintaining computational efficiency. This paper examines the use of Gaussian process machine learning to generalize and enhance the commonly used class of quasi-Linear Parameter Varying models for fast full-envelope simulation while also supporting control system design and analysis with model uncertainty. Gaussian process machine learning is selected because it: can fuse multiple data sets, enables an easy trade-off between data fitting and smoothing, provides model uncertainty quantification, scales well with increasing complexity, and does not generally require starting from a large training data set. To demonstrate the benefits of the approach, a robust stability analysis with Gaussian process uncertainty is shown for a NASA reference design of an electric quad-rotor air-taxi concept vehicle with motor parameter uncertainty.

Gaussian Process↗

DOE OSTI2026

Higher-order LaSDI: Reduced order modeling with multiple time derivatives

Solving complex partial differential equations (PDEs) is essential across scientific disciplines but often requires numerical models that can be prohibitively expensive in time-sensitive applications. Reduced-order models (ROMs) address this challenge by exploiting low-dimensional structure to create fast approximations. The Latent Space Dynamics Identification (LaSDI) framework has demonstrated success in learning ROMs for parameterized PDE families, but remains limited to first-order systems. Here, in this paper, we propose Higher-Order LaSDI (HLaSDI), which extends the LaSDI framework to PDEs with arbitrary order of time derivatives. This generalization significantly expands the applicability of LaSDI-based methods to systems previously outside their scope, including hyperbolic PDEs. We demonstrate HLaSDI’s accuracy and efficiency on several linear and nonlinear benchmark problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Women as a Force Multiplier for Bringing Nuclear Forensic Capabilities to the International Stage

In 2009, the US Department of Energy National Nuclear Security Administration’s (NNSA’s) Defense Nuclear Nonproliferation Program initiated a new nuclear forensics outreach effort under its Confidence Building Measures Program. Little did they know that the timing could not have been better. This article focuses on the early years (2009–2015) of the NNSA’s international nuclear forensics outreach, specifically the efforts and experiences of the women who helped establish this program, building it from a fledgling, bilateral effort into an enduring technical capacity provider engaging with dozens of countries and multilateral organizations. At the onset of the program, nuclear forensics was an emerging priority within the US Government and receiving increased focus from international organizations through high-level diplomatic efforts such as the Nuclear Security Summit and Global Initiative to Combat Nuclear Terrorism. Additionally, working-level initiatives were gaining traction through the International Atomic Energy Agency and the Nuclear Forensics International Technical Working Group. Over the next 6 years, a small team comprising a uniquely large number of women NNSA federal, contract, and national laboratory staff served as key leaders engaging with the international community to strengthen global technical nuclear forensics capacity and best practices. The program continues today under the Nuclear Smuggling Detection and Deterrence Program as Investigation Support. The experiences shared here detail a unique time period when the new technical discipline of nuclear forensics was beginning to mature and gain international traction. The authors have made every effort to remember history correctly and be as inclusive as possible. A wealth of training, guidance, and exercise documentation was developed in the 2009–2015 time frame, much of which still serves as the foundation for today’s even more extensive program and community of dedicated technical and diplomatic practitioners.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRS2014

The Cassini Solstice Mission: Streamlining Operations by Sequencing with PIEs

The Cassini Solstice Mission (CSM) is the second extended mission phase of the highly successful Cassini/Huygens mission to Saturn. Conducted at a much-reduced funding level, operations for the CSM have been streamlined and simplified significantly. Integration of the science timeline, which involves allocating observation time in a balanced manner to each of the five different science disciplines (with representatives from the twelve different science instruments), has long been a labor-intensive endeavor. Lessons learned from the prime mission (2004-2008) and first extended mission (Equinox mission, 2008-2010) were utilized to design a new process involving PIEs (Pre-Integrated Events) to ensure the highest priority observations for each discipline could be accomplished despite reduced work force and overall simplification of processes. Discipline-level PIE lists were managed by the Science Planning team and graphically mapped to aid timeline deconfliction meetings prior to assigning discrete segments of time to the various disciplines. Periapse segments are generally discipline-focused, with the exception of a handful of PIEs. In addition to all PIEs being documented in a spreadsheet, allocated out-of-discipline PIEs were entered into the Cassini Information Management System (CIMS) well in advance of timeline integration. The disciplines were then free to work the rest of the timeline internally, without the need for frequent interaction, debate, and negotiation with representatives from other disciplines. As a result, the number of integration meetings has been cut back extensively, freeing up workforce. The sequence implementation process was streamlined as well, combining two previous processes (and teams) into one. The new Sequence Implementation Process (SIP) schedules 22 weeks to build each 10-week-long sequence, and only 3 sequence processes overlap. This differs significantly from prime mission during which 5-week-long sequences were built in 24 weeks, with 6 overlapping processes.

Vandermey, Nancy↗

NASA NTRS2016

International Research Results and Accomplishments From the International Space Station - A New Compilation

In 2016, the International Space Station (ISS) partnership published the first-ever compilation of international ISS research publications resulting from research performed on the ISS through 2011 (Expeditions 0 through 30). International Space Station Research Accomplishments: An Analysis of Results. From 2000-2011 is a collection of over 1,200 journal publications that describe ISS research in the areas of biology and biotechnology; Earth and space science; educational activities and outreach; human research; physical sciences; technology development and demonstration; and, results from ISS operations. This paper will summarize the ISS results publications obtained through 2011 on behalf of the ISS Program Science Forum that is made up of senior science representatives across the international partnership. NASA's ISS Program Science office maintains an online experiment database (www.nasa.gov/iss- science) that tracks and communicates ISS research activities across the entire ISS partnership, and it is continuously updated by cooperation and linking with the results tracking activities of each partner. It captures ISS experiment summaries and results and includes citations to the journals, conference proceedings, and patents as they become available. This content is obtained through extensive and regular journal and patent database searches, and input provided by the ISS international partners ISS scientists themselves. The International Space Station Research Accomplishments: An Analysis of Results From 2000-2011 is a testament to the research that was underway even as the ISS laboratory was being built. It rejects the scientific knowledge gained from ISS research, and how it impact the fields of science in both space and traditional science disciplines on Earth. Now, during a time when utilization is at its busiest, and with extension of the ISS through at least 2024, the ISS partners work together to track the accomplishments and the new knowledge gained in a way that will impact humanity like no laboratory on Earth. Examples of the highest pro le publications to date from each discipline will also be presented. As ISS research activities and operations continue, scientific data derived from earlier experiments will continuously be re-examined, refined, and assembled with new data and findings, including data from other fields never considered. New results will be produced, allowing breakthroughs in new areas of research and innovative solutions to problems on Earth. The ISS Program Science Forum will continue to capture and report on these results in the form of journal publications, conference proceedings, and patents. We anticipate that successful ISS research will continue to contribute to the science literature in a way that helps to formulate new hypotheses and conclusions that will enable science advancements across a wide range of scientific disciplines both in space and on Earth.

Ruttley, Tara↗

NASA NTRS2011

GLobal Integrated Design Environment

The GLobal Integrated Design Environment (GLIDE) is a collaborative engineering application built to resolve the design session issues of real-time passing of data between multiple discipline experts in a collaborative environment. Utilizing Web protocols and multiple programming languages, GLIDE allows engineers to use the applications to which they are accustomed in this case, Excel to send and receive datasets via the Internet to a database-driven Web server. Traditionally, a collaborative design session consists of one or more engineers representing each discipline meeting together in a single location. The discipline leads exchange parameters and iterate through their respective processes to converge on an acceptable dataset. In cases in which the engineers are unable to meet, their parameters are passed via e-mail, telephone, facsimile, or even postal mail. The result of this slow process of data exchange would elongate a design session to weeks or even months. While the iterative process remains in place, software can now exchange parameters securely and efficiently, while at the same time allowing for much more information about a design session to be made available. GLIDE is written in a compilation of several programming languages, including REALbasic, PHP, and Microsoft Visual Basic. GLIDE client installers are available to download for both Microsoft Windows and Macintosh systems. The GLIDE client software is compatible with Microsoft Excel 2000 or later on Windows systems, and with Microsoft Excel X or later on Macintosh systems. GLIDE follows the Client-Server paradigm, transferring encrypted and compressed data via standard Web protocols. Currently, the engineers use Excel as a front end to the GLIDE Client, as many of their custom tools run in Excel.

Kunkel, Matthew↗

NASA NTRS2016

International Research Results and Accomplishments From the International Space Station

In 2016, the International Space Station (ISS) partnership published the first-ever compilation of international ISS research publications resulting from research performed on the ISS through 2011. The International Space Station Research Accomplishments: An Analysis of Results From 2000-2011 is a collection of summaries of over 1,200 journal publications that describe ISS research in the areas of biology and biotechnology; Earth and space science; educational activities and outreach; human research; physical sciences; technology development and demonstration; and, results from ISS operations. This paper will summarize the ISS results publications obtained through 2011 on behalf of the ISS Program Science Forum that is made up of senior science representatives across the international partnership. NASA's ISS Program Science office maintains an online experiment database (www.nasa.gov/issscience) that tracks and communicates ISS research activities across the entire ISS partnership, and it is continuously updated. It captures ISS experiment summaries and results and includes citations to the journals, conference proceedings, and patents as they become available. The International Space Station Research Accomplishments: An Analysis of Results From 2000-2011 is a testament to the research that was underway even as the ISS laboratory was being built. It reflects the scientific knowledge gained from ISS research, and how it impact the fields of science in both space and traditional science disciplines on Earth. Now, during a time when utilization is at its busiest, and with extension of the ISS through at least 2024, the ISS partners work together to track the accomplishments and the new knowledge gained in a way that will impact humanity like no laboratory on Earth. The ISS Program Science Forum will continue to capture and report on these results in the form of journal publications, conference proceedings, and patents. We anticipate that successful ISS research will continue to contribute to the science literature in a way that helps to formulate new hypotheses and conclusions that will enable science advancements across a wide range of scientific disciplines both in space and on Earth.

Ruttley, Tara M.↗

DOE OSTI2024

Women as a force multiplier for bringing nuclear forensic capabilities to the international stage

In 2009, the U.S. Department of Energy / National Nuclear Security Administration’s (DOE/NNSA) Defense Nuclear Nonproliferation (DNN) Program initiated a new nuclear forensics outreach effort under its Confidence Building Measures Program. Little did they know that the timing could not have been better. This article focuses on the early years (2009-2015) of the NNSA’s international nuclear forensics outreach, specifically the efforts and experiences of the women who helped establish this program, building it from a fledgling bilateral effort into an enduring technical capacity provider engaging with dozens of countries and multilateral organizations. At the onset of the program, nuclear forensics was an emerging priority within the U.S. Government and receiving increased focus from international organizations through high-level diplomatic efforts such as the Nuclear Security Summit and Global Initiative to Combat Nuclear Terrorism. Additionally, working-level initiatives were gaining traction through the International Atomic Energy Agency and the Nuclear Forensics International Technical Working Group. Over the next six years, a small team comprised of a uniquely large number of women NNSA federal, contract, and national laboratory staff served as key leaders engaging with the international community to strengthen global technical nuclear forensics capacity and best practices. The program continues today under the Nuclear Smuggling Detection and Deterrence Program as Investigation Support. The experiences shared here detail a unique time period when the new technical discipline of nuclear forensics was beginning to mature and gain international traction. The authors have made every effort to remember history correctly and be as inclusive as possible. A wealth of training, guidance, and exercises documentation was developed in the 2009-2015 timeframe, much of which still serves as the foundation for today’s even more extensive program and community of dedicated technical and diplomatic practitioners.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRS1982

Developments in high-precision gamma-ray burst source studies

The source location data analyzed by the first and second interplanetary gamma ray burst spacecraft networks are reviewed. The possibilities of additional networks and of related studies in other disciplines, and the prospects for real time optical transient observations and for the definition of gamma ray burst sources by optical transient astronomy are also reviewed.

Cline, T. L.↗

NASA NTRS1983

Developments in high-precision gamma-ray burst source studies

Cline, T. L.↗