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DOE OSTI2023

The Low-Yield Nuclear Monitoring (LYNM) Experimental Science Plan

The Low-Yield Nuclear Monitoring (LYNM) Program is a long-term NNSA research and development effort designed to improve the United States’ explosion monitoring capabilities, particularly with respect to low-yield and potentially evasive underground nuclear testing. The LYNM Program focuses on researching, discovering, and exploiting unique and useful signatures, from all available technologies and sensors (e.g., seismic, acoustic, electromagnetic, gases, and particulates (both stable and radioactive)). Four Department of Energy laboratories participate in LYNM and together are referred to as the ‘quad-lab’. The R&D program execution is performed under NNSA defined structures known as “ventures”. Four science ventures were established: 1) Explosion Source Functions; 2) Containment of Low-Yield Underground Tests; 3) Local Signatures; 4) Dynamic Monitoring Networks. To organize and execute the large field scale experiment a fifth venture was established: 5) Physics Experiment One (PE-1). As part of the LYNM Program, a series of experiments are planned at various scales and levels of venture involvement. These vary from those that involve a subset of labs and/or LYNM ventures (e.g., small experiments), to full quad-lab LYNM Program field-scale integrated experiments. Such experiments may involve chemical explosions with tracer materials or other means of simulating the expected signals from a nuclear explosion. The LYNM Program does not conduct actual nuclear explosions. Since 1992, the U.S. has observed a moratorium on underground nuclear explosions. This document is intended to provide the underlying scientific basis for the LYNM planned experimental work. Each specific LYNM experiment will develop a goals, objectives, and requirements (GOR) plan following the guidance in this document. The LYNM technical staff will define the numbers and types of experiments required over the course of the Program based on technical needs and within funding constraints. As with any scientific experiment series, the number and types of experiments may change based upon the experimental results obtained. An experiment that agrees with models/codes/software signature predictions may need fewer repetitions/variations, depending upon the level of statistical rigor desired, as compared to one in which the predictions and experimental data do not match. The large LYNM field-scale integrated experiments require the longest lead-time for planning, and these are discussed in more detail near the end of this document.

58 GEOSCIENCES↗

DOE OSTI2022

Energy Efficient Material Processing through Automated Process Monitoring and Controls

Smart manufacturing is bound to play a crucial role in reducing global energy consumption while accelerating economic development. This phenomenon is evident in advanced sensing technology developments, data analytics and machine learning/AI, automated controls, cloud computing, etc. The immediate opportunity for smart manufacturing is to improve the energy efficiency of manufacturing operations through innovations in processes and controls. The manufacturing industry still consumes about 30% of total global energy production, which is significant. This program focused on the recommendation of heterogeneous sensors to monitor the Chemical Vapor Infiltration (CVI) process parameters, states, and key performance indices and utilize cloud computing to sort and analyze the real-time data. Learning through data analytics helps guide the control parameters affecting energy usage. The target process in the program is the CVI process at the Honeywell South Bend facility, which is one of the most energy-intensive manufacturing industries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Batteries 2018 Annual Progress Report

This document summarizes the progress of VTO battery R&D projects supported during the fiscal year 2018 (FY 2018). In FY 2018, the DOE VTO battery R&D funding was approximately $101 million. Its R&D focus was on the development of high-energy batteries for PEVs and very high-power devices for hybrid vehicles. The electrochemical energy storage roadmap describes ongoing and planned efforts to develop electrochemical storage technologies for PEVs. To advance battery technology to improve the market penetration of PEVs and hybrid vehicles, the program focuses on overcoming specific technical barriers typically related to the battery’s cost, performance, life (both calendar life and cycle life), its tolerance to abusive conditions, and its recyclability/sustainability. Various battery chemistries are being investigated with that aim.

25 ENERGY STORAGE↗

NASA NTRS1986

Development of pressure containment and damage tolerance technology for composite fuselage structures in large transport aircraft

NASA sponsored composites research and development programs were set in place to develop the critical engineering technologies in large transport aircraft structures. This NASA-Boeing program focused on the critical issues of damage tolerance and pressure containment generic to the fuselage structure of large pressurized aircraft. Skin-stringer and honeycomb sandwich composite fuselage shell designs were evaluated to resolve these issues. Analyses were developed to model the structural response of the fuselage shell designs, and a development test program evaluated the selected design configurations to appropriate load conditions.

Smith, P. J.↗

NASA NTRS1981

Life sciences flight experiments program - Overview

The considered LSFE program focuses on Spacelab life sciences missions planned for the 1984-1985 time frame. Life Sciences Spacelab payloads, launched at approximately 18-months intervals, will enable scientists to test hypotheses from such disciplines as vestibular physiology, developmental biology, biochemistry, cell biology, plant physiology, and a variety of other life sciences. An overview is presented of the LSFE program that will take advantage of the unique opportunities for biological experimentation possible on Spacelab. Program structure, schedules, and status are considered along with questions of program selection, and the science investigator working groups. A description is presented of the life sciences laboratory equipment program, taking into account the general purpose work station, the research animal holding facility, and the plant growth unit.

Berry, W. E.↗

DOE OSTI2016

SRS environmental air surveillance program 1954-2015: General trends

The radiological monitoring program at SRS was established under the DuPont Company in June 1951 and was used as a measurement of the effectiveness of plant controls and as an authoritative record of environmental conditions surrounding the plant. It also served as a method of demonstrating compliance with applicable federal regulations and guidance. This document serves as a general summary of changes made specifically to the environmental air monitoring program since its inception, and a discussion of the general trends seen in the air monitoring program at SRS from 1954 to 2015. Initially, the environmental air surveillance program focused not only on releases from SRS but also on fallout from various weapons testing performed through the end of 1978. Flypaper was used to measure the amount of fallout in the atmosphere during this period, and was present at each of the 10 monitoring stations. By 1959, all site stacks were included in the air monitoring program to determine their contribution to the airborne radioactivity onsite, and the number of air surveillance samplers rose to 18. This trend of an increased number of sampling locations continued to a peak of 35 sampling locations before shifting to a downward trend in the mid-1990s. In 1962, 4 outer-range samplers were placed in Savannah and Macon, GA, and in Greenville and Columbia, SC. Until 1976, air samplers were simply placed around the perimeter of the various operation locations (after 1959, this included stacks to determine their contribution to the airborne radioactivity), with the intent of creating as representative a distribution as possible of the air surrounding operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Summary of Methodology for Mitigating Risks Associated with Licensing and Qualifying AM Nuclear Materials

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program focuses on accelerating the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Laser powder bed fusion (LPBF) is one of the most popular additive manufacturing (AM) processes for fabricating components with intrinsically complex geometries. LPBF was extensively explored for nuclear applications under the previous Transformational Challenge Reactor program. Additionally, Oak Ridge National Laboratory developed and licensed the Peregrine software and larger digital platform that couples machine learning and in situ data collection during AM to detect anomalies and any evolved defects. The digital platform will be critical to (1) the qualification of AM components for nuclear applications that link location-specific data to macroscopic properties and (2) predict final component performance. Current in situ process monitoring tools are valuable for observing the formation of stochastic flaws, but additional data are needed to predict the resulting microstructures and associated material performance. Rapid cooling rates and large thermal gradients have caused large heterogeneities in the microstructure, which cause anisotropy in mechanical performance. The AMMT program is evaluating the best approaches for addressing these heterogeneities and their effect on component performance using a combination of multiscale modeling, enhanced in situ process monitoring, and high throughput experimental testing. This report summarizes strategies for mitigating the risks associated with qualifying AM components, including developing new sensing capabilities for in situ process monitoring and characterizing melt pool solidification and residual stresses to inform multiscale modeling efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2011

Eta Carinae - A Demanding Mistress

Over the past 15 years, a number of observers and modelers have increasingly focused on this massive system that is approaching its end stage, a supernova? a hypernova? When? The discovery by Augusto Damineli that Eta Carinae had a 5.5-year period proved timely as the newly-installed STIS was primed to observe its properties in the visible and ultraviolet. Initial observations occurred on January 1998, and through multiple programs, including the multi-cycle Hubble Treasury program, have sampled changes across two cycles. Now a multi-cycle program, focused on mapping variations in the extended wind-wind collision zones through early 2015, will test 3-D models of the interacting winds. In parallel, studies have been accomplished in X-rays with RXTE and CHANDRA, now in the far infrared with Herschel and from the ground with VLT. Each new observation is helping to peel back the veil of mystery on this massive binary system, but also opening up more questions to be answered. Timely inclusion of laboratory studies and models have greatly enhanced the observational results. We will summarize the latest results including submitted papers and very recent results with Herschel.

Gull, Theodore R.↗

NASA NTRS2001

Living With a Star, the Geospace Mission Definition Team and Aeronomy

To gain an understanding of the Sun-Earth system, including how and why the sun varies, how the earth responds, and the impacts on humanity, research is needed that has a integrated and systematic approach. The Living With a Star (LWS) program represents an important element in this regard both to continued progress in space science in general and in Aeronomy in particular. A fundamental question in Aeronomy is how the variable sun affects the ionosphere, thermosphere, and mesosphere. The LWS program focuses on those areas of scientific understanding that promote progress in areas that have human impact and can be investigated with space borne instruments. The Geospace Mission Definition Team is charged with investigating the science priorities identified by the LWS Science Architecture Team and developing an approach to making the necessary measurements in concert with other missions and programs. An important aspect of this approach is that all LWS measurement programs are operating simultaneously for several years. We will review some of the areas that the LWS SAT have emphasized in Aeronomy, including understanding the effects of solar variability on ionospheric density and irregularities, the effects of solar variability on the mass density of the atmosphere at LEO altitudes, and the effects of solar variability on near-surface temperatures and on ozone distribution.

Kintner, Paul M., Jr.↗

NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗

NASA NTRS2000

X-38 V-132 Free Flight 2 (This is a video tape)

Mr. Aldo Bordano will be presenting details of some of the JSC flight mechanics involvement in the X-38 testing program. Focus shall be on the parafoil system with regards its testing, performance analysis, and GN&C. An excellent example of a recent flight test at Dryden Flight Research Center shall be shown which portrays the system characteristics, sequencing, performance, and testing techniques. The intent is to inform the scientific and engineering communities about the developments in the X-38 parafoil program, as well as invite feedback on potential improvements in testing or systems.

Bordano, Aldo J.↗

NASA NTRS1994

Inlet distortion in engines on VSTOL aircraft

This report presents the results of a research program on inlet distortion in engines on VSTOL aircraft carried out at the MIT Gas Turbine Laboratory during the period Oct. 1989 - Dec. 1993. The program focused on the development of three dimensional flow computational methodology for predicting the effects of nonuniform flow on the performance of aircraft engines in VSTOL aircraft, the development of a three dimensional instability analysis of flow in multistage axial compressors, and the preliminary applications of these newly developed methodologies for elucidating the effects of flow three dimensionality. The accomplishments of the program are brought out when the current status of predictive capabilities for three dimensional flow instabilities in compressors is assessed against that in 1989.

Tan, Choon S.↗

DOE OSTI2015

Gary Laughlin IHNS Intro to 2015 HPC Annual Report

The International, Homeland, and Nuclear Security (IHNS) Program Management Unit (PMU) oversees a broad portfolio of Sandia’s programs in areas ranging from global nuclear security to critical asset protection. We use science and technology, innovative research, and global engagement to counter threats, reduce dangers, and respond to disasters. The PMU draws on the skills of scientists and engineers from across Sandia. Our programs focus on protecting US government installations, safeguarding nuclear weapons and materials, facilitating nonproliferation activities, securing infrastructures, countering chemical and biological dangers, and reducing the risk of terrorist threats. We conduct research in risk and threat analysis, monitoring and detection, decontamination and recovery, and situational awareness. We develop technologies for verifying arms control agreements, neutralizing dangerous materials, detecting intruders, and strengthening resiliency. Our programs use Sandia’s High-Performance Computing resources for predictive modeling and simulation of interdependent systems, for modeling dynamic threats and forecasting adaptive behavior, and for enabling decision support and processing large cyber data streams. In this report, we highlight four advanced computation projects that illustrate the breadth of the IHNS mission space.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2026

Computational Modeling of Atmospheric Processes at Texas Southern University

Texas Southern University (TSU) is strengthening its research program in atmospheric chemistry and physics with a climate science emphasis by leveraging partnerships with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility, Brookhaven National Laboratory (BNL), and the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This RDPP-supported program focuses on secondary organic aerosols (SOAs) and reactive atmospheric species that influence cloud formation, precipitation processes, and radiative forcing. SOAs play a critical role in cloud microphysics and Earth’s energy balance, yet the chemical and physical mechanisms governing SOA–cloud interactions remain a significant source of uncertainty in predictive climate models. Through computational modeling, observational data analysis, and national laboratory collaboration, this program develops a skilled cohort of students trained in atmospheric science, environmental data analysis, and climate-relevant modeling. These research experiences build technical competencies that are transferable to careers in government laboratories, academia, and industry. By engaging students from historically underrepresented communities in high-impact climate research, TSU expands participation in the atmospheric sciences workforce while contributing meaningful scientific insights to DOE-supported ARM research activities. This partnership strengthens national capacity in climate science and supports the development of the next generation of atmospheric researchers.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

A summary of porous tube plant nutrient delivery system investigations from 1985 to 1991

The Controlled Ecological Life Support System (CELSS) Program is a research effort to evaluate biological processes at a one person scale to provide air, water, and food for humans in closed environments for space habitation. This program focuses currently on the use of conventional crop plants and the use of hydroponic systems to grow them. Because conventional hydroponic systems are dependent on gravity to conduct solution flow, they cannot be used in the microgravity of space. Thus, there is a need for a system that will deliver water and nutrients to plant roots under microgravity conditions. The Plant Space Biology Program is interested in investigating the effect that the space environment has on the growth and development of plants. Thus, there is also a need to have a standard nutrient delivery method for growing plants in space for research into plant responses to microgravity. The Porous Tube Plant Nutrient Delivery System (PTPNDS) utilizes a hydrophilic, microporous material to control water and nutrient delivery to plant roots. It has been designed and analyzed to support plant growth independent of gravity and plans are progressing to test it in microgravity. It has been used successfully to grow food crops to maturity in an earth-bound laboratory. This document includes a bibliography and summary reports from the growth trials performed utilizing the PTPNDS.

Dreschel, T. W.↗

DOE OSTI2019

Sandia National Laboratories Early Career University Faculty Mentoring Program in International Safeguards

An international safeguards mentoring program was established by Sandia National Laboratories (SNL) for early career university faculty. The inaugural year of the program focused on course material development and connecting faculty to experts at national laboratories. Two faculty members were selected for participation; one developed a safeguards-by-design course, and the other created lecture material related to unmanned robotic systems in safeguards for integration in existing courses. Faculty members were paired with SNL subject matter experts based on the topic of their individual projects. The program also included a two week visit to SNL. The structure of this program not only supported the development of new course material, but also provided junior faculty members with an opportunity to make connections and build collaborations in the field of international safeguards. Programs like this are important for professional development of faculty members and to help strengthen connections between universities and the national laboratories.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2024

Supercharge NY

The Energy Program for Innovation Clusters (EPIC) Supercharge NY enabled The Clean Fight to execute an inaugural accelerator program focused on enabling world-class, growth-stage energy storage companies to successfully scale deployments and establish domestic manufacturing pathways in New York State. The Clean Fight has developed and tested a successful accelerator model designed to reduce the barriers growth-stage climate tech companies face by collapsing the sales cycle to scaling solutions at speed. The Clean Fight’s Supercharge NY project allowed for the exploration into the understanding of New York-focused energy storage opportunities, challenges, and methods for enabling successful projects. The Clean Fight’s Supercharge NY project enabled high-touch matchmaking with industry leading customer and capital partners, technical assistance to facilitate scaling supply chain and manufacturing capacity, and access to non-dilutive funding for first-of-a-kind or demonstration projects in New York State. The results of the program provide a public benefit by accelerating deployments of energy storage to provide value-added energy services and sustainability benefits to communities while boosting economic opportunity and job creation for all.

25 ENERGY STORAGE↗