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At least 937 records · Page 52

Continuing Development of a Collaborative Plan to Further Engage South Dakota in NASA's Earth Science Enterprise

An ongoing set of research planning activities have occurred in South Dakota as a consequence of the past two years of NASA-EPSCoR Preparation Grants. During this time a group of approximately 60 scientists, engineers, and university administrators in South Dakota have been directly involved as "theme team" members in a series of five all-day meetings to identify the research and technological priorities that are consistent both with NASA-ESE's interests and the State's expertise. Institutions represented within the group's membership include: South Dakota School of Mines & Technology, South Dakota State University, Augustana College, University of South Dakota, USGS EROS Data Center, Si ranks College, Santa Gleska University, Sisseton Wahpeton Community College, USGS Water Resources Division, US National Weather Service, and the SD Department of Environment & Natural Resources. Many of these organizations are also members and affiliates of the SD Space Grant Consortium. The evolving plan has been guided by the following desirable actions: 1. To establish new contacts and strengthen existing linkages with NASA Centers, relevant NASA researchers, and key personnel at the USGS EROS Data Center. 2. To promote participation from the State's major research institutions, State agencies, and relevant businesses in South Dakota that are interested in strengthening our scientific and technological enterprises. 3. To develop the State's scientific talent and infrastructure for enhanced competitiveness in research, development, and technology-based economic development. 4. To encourage greater participation by under represented groups, especially Native Americans, in scientific education and research. 5. To build greater public and political support in South Dakota for the overall science, engineering, and technology enterprise. 6. To communicate the benefits of current and future NASA programs to the progress and development of South Dakota, the Northern Great Plains Region, and the Nation.

Farwell, Sherry O.↗

NASA information systems commonality and convergence

Efforts to identify high payback functions performed by the Office of Space Science Applications (OSSA) data systems package existing operationally proven implementations as system building blocks and foster their use in the OSSA environment. An overview is given of the current state of OSSA data systems and the major challenges facing system developers over the next five years. Current trends in system commonality are discussed, and development is examined in the context of system design. Central system engineering approaches to solving the commonality and interoperability challenges are described. Efforts to package three diverse building blocks and to foster their reuse are documented.

Handley, Thomas H., Jr.↗

FIBER-TEX 1991: The Fifth Conference on Advanced Engineering Fibers and Textile Structures for Composites

This document is a compilation of papers presented at a joint NASA/North Carolina State University/DoD/Clemson University/Drexel University conference on Fibers, Textile Technology, and Composites Structures held at the College of Textiles Building on Centennial Campus of North Carolina State University, Raleigh, North Carolina on October 15-17, 1991. Conference papers presented information on advanced engineering fibers, textile processes and structures, structural fabric production, mechanics and characteristics of woven composites, pultruded composites, and the latest requirements for the use of textiles in the production of composite materials and structures.

Buckley, John D.↗

NASA's Design and Development of a Field Goniometer Instrument Using Solid Works

With NASA suffering severe funding cutbacks, engineers at NASA are required to produce state-of-the-art hardware with limited personnel and financial resources. In light of these constraints, the new NASA mandate is to build better, faster and cheaper. In April of 1998, Stennis Space Center's Commercial Remote Sensing Program contracted to the Systems Engineering Division at NASA Ames Research Center to develop a device known as a Field Goniometer. A Field Goniometer is a device that measures bi-directional reflectance of a target, such as vegetation, relative to the sun and an imaging system in an aircraft or spacecraft. The device is able to provide a spectral fingerprint of the surface it is measuring in wavelengths from 350nm-2500nm using a hyperspectral imager. To accomplish this project, several obstacles had to be overcome. First, the design had to be completed in less than four months. Second, due to the complexity of the design, the use of solid modeling was highly desirable but most of the group's solid modelers were assigned to other jobs. Third, the amount of funding available from the customer was one half to one third the funding typically expended for a job of this nature. Our choices for this project were to design with standard 2-D CAD systems currently used in-house or train additional engineers on our existing solids package or purchase a new solid model package. The use of a 2D CAD system was very undesirable due to the complexity of the design. Using our existing solids modeler would have required a learning curve for our engineers that would be incompatible with our schedule. Prior to this project, a member of our design group researched the solid modeling industry and decided to purchase SolidWorks. After examining the product for ease of use, modeling capability, training time required and cost, we decided our highest probability of success would be to design with Solidworks. During the design phase, our fabrication group was able to provide input at the very early stages, which added significant benefit to the final product. Fabrication cost and schedule savings have been realized by having complex part geometries translated directly from the SolidWorks design models to Surfcam and other computer-aided manufacturing (CAM) software. This direct model translation capability optimized the fabrication processes. The end result was that we were able to successfully complete the project on time and on budget. Other advantages of using SolidWorks, as cited by the design team, include a rapid negotiation of the initial learning curve, the ability to develop solid model hardware prototypes (used to communicate the design intent to both the customer and the fabricator), and the ability to work as a team collaborating on a large, complex model. These types of tools and efforts represent our response to NASA's challenge to produce higher quality products within shorter design and fabrication times.

Turner, Mark↗

Optimizing Facility Operations by Applying Machine Learning to the Army Reserve Enterprise Building Control System (Final Report)

Thousands of U.S. Department of Defense (DoD) buildings have building automation systems (BASs) and/or advanced meters. Although these systems have a wealth of data, performance optimization requires time and expertise to review and act on that information. Machine learning (ML) can provide automated and actionable insights to controls operators. This demonstration implemented proven ML methods on the Army Reserve Enterprise Building Control System. ML refers to algorithms that “learn” from data and improve their performance on a given task over time. In the buildings domain these tasks range from predicting future energy consumption, to identifying operational issues before faults occur, to optimizing control decisions. To learn, ML requires input data, which – for buildings – typically consists of instrument data such as energy consumption data and subsystem controls information such as set-point temperatures, and context data consisting of information such as the physical location of the building, the area of the building, and the weather. ML models use the relationships learned from the input data to make predictions with new, previously unseen, data. The team was able to investigate and successfully implement the following ML use cases: labeling consumption data as anomalous or non-anomalous; baseline whole-building load prediction (unknown fault status); fault detection (validation not possible); and site prioritization for energy-related projects. Due to the constraints of the project, interventions were not able to be implemented during the demonstration; therefore, assessments of operational cost savings and maintenance avoided could not be performed. The project has been presented at two leading national building conferences and two additional publications to peer-reviewed journals are currently in preparation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Site-specific Design Case Study for Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels

Hydrothermal liquefaction (HTL) is a thermal process that converts wet biomass to renewable hydrocarbon fuel blendstocks (i.e., renewable naphtha, renewable diesel, and sustainable aviation fuel (SAF)). It can utilize a wide range of pure and blended wet feedstocks, including sewage sludge from water resource recovery facilities (WRRF), food and agriculture wastes, algae, fats, oils and greases (FOG) and blends of dry and wet wastes/feedstocks. Historically, techno-economic analysis (TEA) and annual state of technology (SOT) assessments with standard economic assumptions used by the Bioenergy Technologies Office (BETO) were conducted for the wet waste HTL pathway leveraging experimental data collected from Pacific Northwest National Laboratory’s (PNNL) continuous flow reactor systems. The objective of the SOT assessment has been to guide and track progress of BETO’s HTL research and development (R&D) toward reduced cost and greenhouse gas (GHG) emissions for the pathway. However, gaps exist between BETO’s traditional SOT updates and the needs of key external stakeholders that – if addressed – will accelerate technology adoption. This Business Case Study aims to bridge this gap by providing an updated design, TEA, and LCA based on PNNL’s FY23 R&D with added analyses and information that provide enhanced relevance for stakeholders of the HTL technology. This includes specific siting, regional wet waste resource inventory and transportation cost analyses, fuel market information, sustainable fuel policy impacts, economic metrics of net present value (NPV) and internal rate of return (IRR), greenhouse gas (GHG) emissions analysis, and statistical analysis of cost and technical uncertainties of the HTL plant design. The study focuses on the “Detroit combined statistical area (CSA)” region for siting of a wet waste HTL plant adjacent to the Great Lakes Water Authority (GLWA) facility with guidance from industry participants. Regional resource and siting analyses were conducted to identify feedstock availability, scale, and cost, as well as a beneficial site location. TEA with detailed rigorous capital cost estimation for the specific site application was conducted to evaluate the key economic metrics of most value to industrial partners. These include total capital investment, operating costs, minimum fuel selling price (MFSP) of the biocrude and fuel blendstock, and NPV and internal rate of return IRR with sustainable fuel credits. Life cycle analysis was conducted to evaluate the supply chain greenhouse gas (GHG) emissions for the wet waste HTL process as compared with petroleum derived diesel. This study is also informed by years of R&D and process de-risking learnings and was conducted with a basic engineering HTL plant design and costing that akin to a “first-of-a-kind” plant economics. This differs from our conventional “nth plant ” SOT assessments. Specifically, the HTL process model has been updated with more operationally reliable methods for feed heating and phase separations. Further, we have implemented additional spare equipment for redundancy, a more rigorous installed equipment cost estimation approach, and additional costs associated with feed formatting and delivery, building, piping and site development. An Excel-based cost sheet based on the basic engineering design is also released alongside the report that allows users to conduct customized TEA with their own feed composition and financial assumptions.

09 BIOMASS FUELS↗

Supporting data for Site-specific Design Case Study for Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels

Hydrothermal liquefaction (HTL) is a thermal process that converts wet biomass to renewable hydrocarbon fuel blendstocks (i.e., renewable naphtha, renewable diesel, and sustainable aviation fuel (SAF)). It can utilize a wide range of pure and blended wet feedstocks, including sewage sludge from water resource recovery facilities (WRRF), food and agriculture wastes, algae, fats, oils and greases (FOG) and blends of dry and wet wastes/feedstocks. Historically, techno-economic analysis (TEA) and annual state of technology (SOT) assessments with standard economic assumptions used by the Bioenergy Technologies Office (BETO) were conducted for the wet waste HTL pathway leveraging experimental data collected from Pacific Northwest National Laboratory’s (PNNL) continuous flow reactor systems. The objective of the SOT assessment has been to guide and track progress of BETO’s HTL research and development (R&D) toward reduced cost and greenhouse gas (GHG) emissions for the pathway. However, gaps exist between BETO’s traditional SOT updates and the needs of key external stakeholders that – if addressed – will accelerate technology adoption. This Business Case Study aims to bridge this gap by providing an updated design, TEA, and LCA based on PNNL’s FY23 R&D with added analyses and information that provide enhanced relevance for stakeholders of the HTL technology. This includes specific siting, regional wet waste resource inventory and transportation cost analyses, fuel market information, sustainable fuel policy impacts, economic metrics of net present value (NPV) and internal rate of return (IRR), greenhouse gas (GHG) emissions analysis, and statistical analysis of cost and technical uncertainties of the HTL plant design. The study focuses on the “Detroit combined statistical area (CSA)” region for siting of a wet waste HTL plant adjacent to the Great Lakes Water Authority (GLWA) facility with guidance from industry participants. Regional resource and siting analyses were conducted to identify feedstock availability, scale, and cost, as well as a beneficial site location. TEA with detailed rigorous capital cost estimation for the specific site application was conducted to evaluate the key economic metrics of most value to industrial partners. These include total capital investment, operating costs, minimum fuel selling price (MFSP) of the biocrude and fuel blendstock, and NPV and internal rate of return IRR with sustainable fuel credits. Life cycle analysis was conducted to evaluate the supply chain greenhouse gas (GHG) emissions for the wet waste HTL process as compared with petroleum derived diesel. This study is also informed by years of R&D and process de-risking learnings and was conducted with a basic engineering HTL plant design and costing that akin to a “first-of-a-kind” plant economics. This differs from our conventional “nth plant ” SOT assessments. Specifically, the HTL process model has been updated with more operationally reliable methods for feed heating and phase separations. Further, we have implemented additional spare equipment for redundancy, a more rigorous installed equipment cost estimation approach, and additional costs associated with feed formatting and delivery, building, piping and site development. An Excel-based cost sheet based on the basic engineering design is also released alongside the report that allows users to conduct customized TEA with their own feed composition and financial assumptions.

Li, Shuyun↗

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗

JGI Plant Transformation Workshop, May 20-21, 2025

Domestic biomass crops such as sorghum, switchgrass, Miscanthus, and poplar can provide United States industries with renewable feedstocks while also supporting low-input farming systems and strengthening supply chains for biofuels, biochemicals and biomaterials. The U.S. leads globally in biomass crop genomics, yet progress in engineering traits is constrained by slow, genotype-dependent transformation methods and lengthy Design-Build-Test-Learn (DBTL) cycles. At a May 2025 workshop, a panel of experts recommended establishing a DOE Plant Transformation Capability (PTC) to overcome these barriers. The PTC would unite two missions: advancing research to achieve genotype-independent, automated methods, and delivering scalable transformation services through a user-facility model. With expected gains of 10–100x in efficiency, including transformation and cost reduction, the PTC would accelerate the path from discovery to engineered plants, expand community access and training, and support downstream applications and workflows including field trials and regulatory navigation. By enabling rapid and predictable crop engineering, the PTC would strengthen U.S. supply chains, enhance industrial competitiveness, and ensure that DOE’s genomic investments deliver national impact.

09 BIOMASS FUELS↗

Lean Model-Based Systems Engineering on the NASA High-Density Vertiplex Subproject

The High Density Vertiplex (HDV) subproject of NASA’s Advanced Air Mobility (AAM) project adopted Model-Based Systems Engineering (MBSE) in July of 2020, prior to subproject formulation. A small and lean team of HDV Systems Engineers (SE) are utilizing MagicDraw to execute NASA SE processes via MBSE. The SEs learned how to use MagicDraw from scratch and HDV is the first project for which the SEs have utilized MagicDraw. This presentation will demonstrate project technical execution via MBSE, utilizing the digital elements built into the SysML (Systems Modeling Language). SysML provides a model-centric means of carrying out the NASA SE common technical processes by providing tools for complete system modeling, including requirements and interface management and design capture. The authors also leverage and extend SysML to perform other SE tasks, such as Verification and Validation (V&V) tracking. MBSE has two main purposes for HDV: 1) documenting the subproject’s logical architecture for distribution outside of the subproject, 2) capturing the subproject’s physical architecture in a single-source-of-truth for use by the subproject’s members. This presentation details the challenges, lessons learned, and solutions that were encountered in implementing MBSE in the first iteration on a multi-iteration, full-lifecycle design, build, fly project.

systems engineering↗

Enhanced modeling features within TREETOPS

The original motivation for TREETOPS was to build a generic multi-body simulation and remove the burden of writing multi-body equations from the engineers. The motivation of the enhancement was twofold: (1) to extend the menu of built-in features (sensors, actuators, constraints, etc.) that did not require user code; and (2) to extend the control system design capabilities by linking with other government funded software (NASTRAN and MATLAB). These enhancements also serve to bridge the gap between structures and control groups. It is common on large space programs for the structures groups to build hi-fidelity models of the structure using NASTRAN and for the controls group to build lower order models because they lack the tools to incorporate the former into their analysis. Now the controls engineers can accept the hi-fidelity NASTRAN models into TREETOPS, add sensors and actuators, perform model reduction and couple the result directly into MATLAB to perform their design. The controller can then be imported directly into TREETOPS for non-linear, time-history simulation.

Vandervoort, R. J.↗

Prototype Common Bus Spacecraft: Hover Test Implementation and Results

In order to develop the capability to evaluate control system technologies, NASA Ames Research Center (Ames) began a test program to build a Hover Test Vehicle (HTV) - a ground-based simulated flight vehicle. The HTV would integrate simulated propulsion, avionics, and sensors into a simulated flight structure, and fly that test vehicle in terrestrial conditions intended to simulate a flight environment, in particular for attitude control. The ultimate purpose of the effort at Ames is to determine whether the low-cost hardware and flight software techniques are viable for future low cost missions. To enable these engineering goals, the project sought to develop a team, processes and procedures capable of developing, building and operating a fully functioning vehicle including propulsion, GN&C, structure, power and diagnostic sub-systems, through the development of the simulated vehicle.

Hine, Butler Preston↗

Engineered Polymer Architectures for Thermo–Responsive Desiccants in Dehumidification Applications

Humidity control is relevant to many processes in buildings and manufacturing and is responsible for over 600 million tons of CO 2 annually. As such, desiccants that can efficiently remove moisture from air can greatly reduce emissions. A new class of desiccant materials, thermo–responsive desiccants, has been of increased interest in the literature. These materials are generally based on thermo–responsive polymers and exhibit a temperature–dependent isotherm, an attribute that is small in traditional desiccants. In this work, seven key parameters needed to create an effective thermo–responsive polymer desiccant are identified using a combination of modeling and experimental data. Further, it is found that more thermo–responsiveness is not necessarily better for energy efficiency, and that an optimal, “medium” value is desired. Additionally, polymer composition and architecture play key roles in adjusting the seven key parameters. Finally, based on findings from both modeling and experimental work, guidelines on synthesizing future thermo–responsive polymer desiccants are presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Record high room temperature resistance switching in ferroelectric-gated Mott transistors unlocked by interfacial charge engineering

Abstract The superior size and power scaling potential of ferroelectric-gated Mott transistors makes them promising building blocks for developing energy-efficient memory and logic applications in the post-Moore’s Law era. The close to metallic carrier density in the Mott channel, however, imposes the bottleneck for achieving substantial field effect modulation via a solid-state gate. Previous studies have focused on optimizing the thickness, charge mobility, and carrier density of single-layer correlated channels, which have only led to moderate resistance switching at room temperature. Here, we report a record high nonvolatile resistance switching ratio of 38,440% at 300 K in a prototype Mott transistor consisting of a ferroelectric PbZr 0.2 Ti 0.8 O 3 gate and an R NiO 3 ( R : rare earth)/La 0.67 Sr 0.33 MnO 3 composite channel. The ultrathin La 0.67 Sr 0.33 MnO 3 buffer layer not only tailors the carrier density profile in R NiO 3 through interfacial charge transfer, as corroborated by first-principles calculations, but also provides an extended screening layer that reduces the depolarization effect in the ferroelectric gate. Our study points to an effective material strategy for the functional design of complex oxide heterointerfaces that harnesses the competing roles of charge in field effect screening and ferroelectric depolarization effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

General Aviation Pilot Advisory and Training System (GAPATS)

The goal of this project is to achieve a validated General Aviation Pilot Advisor and Training System (GAPATS) engineering prototype, implemented according to commercial software standards and Federal Aviation Administration (FAA) issues of certification. Phase 2 builds on progress during Phase 1, which exceeded proposed objectives. The basic technology has been transferred from previous NASA research (1989 to 1994). We anticipate a commercially licensable prototype, validated by pilots in a flight simulator and in a light twin-engine research aircraft for FAA certification, by January 1998.

Painter, John↗

The Ares Projects: Building America's Future in Space

NASA's Constellation Program is depending on the Ares Projects to deliver the crew and cargo launch capabilities needed to send human explorers to the Moon and beyond. In 2009, the Ares Projects plan to conduct the first test flight of Ares I, Ares I-X; the first firing of a five-segment development solid rocket motor for the Ares I first stage; building the first integrated Ares I upper stage; continue component testing for the J-2X upper stage engine; and perform more-detailed design studies for the Ares V cargo launch vehicle. Ares I and V will provide the core space launch capabilities needed to continue providing crew and cargo access to the International Space Station (ISS), and to build upon the U.S. history of human spaceflight to the Moon and beyond.

Cook, Stephen A.↗

STEM Education Efforts in the Ares Projects

According to the National Science Foundation, of the more than 4 million first university degrees awarded in science and engineering in 2006, students in China earned about 21%, those in the European Union earned about 19%, and those in the United States earned about 11%. Statistics like these are of great interest to NASA's Ares Projects, which are responsible for building the rockets for the U.S. Constellation Program to send humans beyond low-Earth orbit. Science, technology, engineering, and mathematics students are essential for the long-term sustainability of any space program. Since the Projects creation, the Ares Outreach Team has used a variety of STEM-related media, methods, and materials to engage students, educators, and the general public in Constellation's mission. Like Project Apollo, the nation s exploration destinations and the vehicles used to get there can inspire students to learn more about STEM. Ares has been particularly active in public outreach to schools in Northern Alabama; on the Internet via outreach and grade-specific educational materials; and in more informal social media settings such as YouTube and Facebook. These combined efforts remain integral to America s space program, regardless of its future direction.

Doreswamy, Rajiv↗

Analysis of Space-Conditioning Loads in Commercial Buildings

Space conditioning end-uses, which include heating, cooling, and ventilation, represent a significant fraction of commercial building energy use, with a wide variety of heating and cooling technology options available in the market. In the interest of improving the overall efficiency of heating, ventilation and air-conditioning (HVAC) technologies, governments, utilities and private sector entities have implemented a variety of market transformation policies that aim to influence consumer purchase decisions. To evaluate the costs and benefits of such programs, analysts typically postulate a hypothetical default equipment choice, and compare it to one that provides comparable service with lower energy and/or power use. The corresponding reduced operating cost provides a benefit that offsets the potential higher cost of improved efficiency. Typically, life-cycle cost or cash-flow analyses are used to quantify the net economic benefit. These analyses require the capability to assess how a given equipment design would perform across a broad range of characteristics, both of the building and of the local weather. While these assessments can be performed using customized building simulations, it is generally not practical to develop and validate detailed building simulation code to cover all the potential variations of equipment design and installation. An alternative, and somewhat simpler, approach is to solely use detailed building simulations to generate time series of heating and cooling loads in commercial buildings. These loads can then be used as input to more detailed, stand-alone engineering models that simulate HVAC system performance under different equipment designs. This approach was used to evaluate a range of high-efficiency commercial packaged air conditioner design options for the Department of Energy’s Appliance and Equipment Standards Program (DOE-EERE 2015). While there may be some loss of precision relative to full simulation, the accuracy of this approach is sufficient for practical applications of cost-benefit analysis. This report describes the development of a database of commercial building heating and cooling loads, generated using the EnergyPlus software package, a whole building energy use model supported by the Department of Energy (DOE-EERE 2020a). EnergyPlus takes as input a set of configuration files that describe the building itself (size, zoning, envelope characteristics, etc.) and the various systems within it (HVAC, lighting, water heating, etc.). This analysis uses a publicly available collection of commercial reference buildings (CRB), comprised of sixteen building types and three vintages (DOE-EERE 2020b; Deru et al 2011). Each building is simulated in eighteen different locations, covering a wide range of climatic conditions. The prototype building description files assign the type of HVAC equipment used, and capacities across climate zones.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗