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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 253 records · Page 14

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NASA NTRS2006

Built But Not Used, Needed But Not Built: Ground System Guidance Based On Cassini-Huygens Experience

These reflections share insight gleaned from Cassini-Huygens experience in supporting uplink operations tasks with software. Of particular interest are developed applications that were not widely adopted and tasks for which the appropriate application was not planned. After several years of operations, tasks are better understood providing a clearer picture of the mapping of requirements to applications. The impact on system design of the changing user profile due to distributed operations and greater participation of scientists in operations is also explored. Suggestions are made for improving the architecture, requirements, and design of future systems for uplink operations.

telecommunications↗

NASA NTRS2014

Visual Image Sensor Organ Replacement

This innovation is a system that augments human vision through a technique called "Sensing Super-position" using a Visual Instrument Sensory Organ Replacement (VISOR) device. The VISOR device translates visual and other sensors (i.e., thermal) into sounds to enable very difficult sensing tasks. Three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. Because the human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns, the translation of images into sounds reduces the risk of accidentally filtering out important clues. The VISOR device was developed to augment the current state-of-the-art head-mounted (helmet) display systems. It provides the ability to sense beyond the human visible light range, to increase human sensing resolution, to use wider angle visual perception, and to improve the ability to sense distances. It also allows compensation for movement by the human or changes in the scene being viewed.

Maluf, David A.↗

NASA NTRS2019

Integrated Research Plan to Assess the Combined Effects of Space Radiation, Altered Gravity, and Isolation and Confinement on Crew Health and Performance: Implementation Strategy

This document supplements the white paper titled CBS Integrated Research Plan: Problem Statement. The Problem Statement describes why it is important to implement a fully integrated research plan to derive risk estimates for the combined, potentially synergistic, effects of the three major spaceflight hazards (space radiation; isolated, confined, and extreme environments; altered gravity). These risk estimates will help establish acceptable maximum decrement or change in a physiological or behavioral parameter during or after spaceflight, and the acceptable limit of exposure to the combined spaceflight hazards. This Implementation Strategy describes how the research plan will accomplish the CBS Integrated Research Plan goals. The Implementation Strategy includes approaches to evaluate relationships among biological responses underlying three risks that are managed by three of NASA’s Human Research Project (HRP) organizational “elements”. This CBS (Acute effects of radiation on CNS, BMed, Sensorimotor) Integrated Research Plan also identifies strategies to monitor and mitigate decrements to operationally relevant performance. Currently, the strategy that was initiated in 2018, includes an eight-year research plan and a four-year validation plan that extend to the year 2030. Once the monitoring tools and countermeasures are developed, they will be validated and refined during four years of early exploration missions. The planned tasks and their associated research products and deliverables have been mapped to the individual research emphases to clearly demonstrate how each research area helps ensure crew health and safety during exploration missions.

Susan Steinberg↗

DOE OSTI2022

Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps

While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as many-to-many. That is, a single input can potentially yield many different outputs (whether due to noise, imperfect measurement, or intrinsic stochasticity in the process) and many different inputs can yield the same output (that is, the map is not injective). For example, imagine a sentiment analysis task where, due to linguistic ambiguity, a single statement can have a range of different sentiment interpretations while at the same time many distinct statements can represent the same sentiment. When modeling such a multivalued function $f: X \rightarrow Y$, it is frequently useful to be able to model the distribution on $f(x)$ for specific input $x$ as well as the distribution on fiber $f^{-1}(y)$ for specific output $y$. Such an analysis helps the user (i) better understand the variance intrinsic to the process they are studying and (ii) understand the range of specific input $x$ that can be used to achieve output $y$. Following existing work which used a fiber bundle framework to better model many-to-one processes we describe how morphisms of fiber bundles provide a template for building models which naturally capture the structure of many-to-many processes.

Coda, Elizabeth D.↗

DOE OSTI2020

Optimization of the Post-Operational Phase on Two Belgian Multi-Unit Nuclear Power Plants: the Case of the Non-Fissile Irradiated Core Items - 20156

The current legal framework in Belgium foresees the progressive phase out of nuclear power between October 2022 (Doel 3) and December 2025 (Doel 2). Upon its definitive shutdown, each unit of the Tihange and Doel sites will enter a Post-Operational Phase (POP) and be prepared for its Decontamination and Decommissioning (D and D). Prior to obtaining the D and D license, the Operator Electrabel is legally required to remove any non-fissile irradiated core items stored in the deactivation pools. The non-fissile irradiated core items consist essentially of control rods, poison rods and source thimbles as well as thimble plugs and foreign materials irradiated during operation: - Their significant content in highly radiant radionuclides (up to 6 TBq of Co-60 per kg of irradiated material) renders all existing operational waste management processes inadequate due to insufficient biological shielding; - Their high concentrations in long-lived radionuclides call for their disposal in a geological repository for which no final design nor waste acceptance criteria are expected prior to 2050. Uncertainties in the Belgian energy supply and security, however, require the Operator to be prepared for a partial nuclear phase out, where one or more units would benefit from lifetime extension while the remaining units would undergo decommissioning. The present paper aims at presenting how Electrabel, in partnership with Tractebel, addressed this challenge by maximizing the use of synergies within the respective sites as well as between both sites themselves, all the while accounting for site specificities. The most recent results and state of progress of the project will be detailed and the first lessons learned will be shared. The project has been split in multiple tasks and phased as follows: - An inventory phase aimed at mapping the contents, origin, composition and history of the non-fissile irradiated core items; - A pre-characterization phase based on neutron activation models; - A waste sorting phase aimed at separating waste forms for which an evacuation route exists from those for which such route does not exist; - A feasibility phase aimed at exploring all possible scenarios for the management of non-fissile irradiated core items and identifying the optimal feasible solution for each site; - A preparation phase (currently ongoing), developing further the optimal solution and ensuring that back-up solutions are available for any foreseeable change of context (licensing issue, modification in the nuclear phase-out program, etc.) and initiating early contacts with potential subcontractors for segmentation works and cask manufacturers, as well as the Belgian regulatory body and waste management agency. This phase also foresees the investigation of destructive and non-destructive radiological measurements to support the detailed characterization of the waste forms; - A realization phase (future work). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Targeted Adaptive Design

Modern advanced manufacturing and advanced materials design often require searches of relatively high-dimensional process control parameter spaces for settings that result in optimal structure, property, and performance parameters. The mapping from the former to the latter must be determined from noisy experiments or from expensive simulations. Here, we abstract this problem to a mathematical framework in which an unknown function from a control space to a design space must be ascertained by means of expensive noisy measurements, which locate control settings generating desired design features within specified tolerances, with quantified uncertainty. We describe targeted adaptive design (TAD), a new algorithm that performs this sampling task efficiently. TAD creates a Gaussian process surrogate model of the unknown mapping at each iterative stage, proposing a new batch of control settings to sample experimentally and optimizing the updated expected log-predictive probability density of the target design. TAD either stops upon locating a solution with uncertainties that fit inside the tolerance box or uses a measure of expected future information to determine that the search space has been exhausted with no solution. TAD thus embodies the exploration-exploitation tension in a manner that recalls, but is essentially different from, Bayesian optimization and optimal experimental design.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Scalable Bayesian optimization with randomized prior networks

Several fundamental problems in science and engineering consist of global optimization tasks involving unknown high-dimensional (black-box) functions that map a set of controllable variables to the outcomes of an expensive experiment. Bayesian Optimization (BO) techniques are known to be effective in tackling global optimization problems using a relatively small number objective function evaluations, but their performance suffers when dealing with high-dimensional outputs. To overcome the major challenge of dimensionality, here we propose a deep learning framework for BO and sequential decision making based on bootstrapped ensembles of neural architectures with randomized priors. Using appropriate architecture choices, we show that the proposed framework can approximate functional relationships between design variables and quantities of interest, even in cases where the latter take values in high-dimensional vector spaces or even infinite-dimensional function spaces. In the context of BO, we augmented the proposed probabilistic surrogates with re-parameterized Monte Carlo approximations of multiple-point (parallel) acquisition functions, as well as methodological extensions for accommodating black-box constraints and multi-fidelity information sources. We test the proposed framework against state-of-the-art methods for BO and demonstrate superior performance across several challenging tasks with high-dimensional outputs, including a constrained multi-fidelity optimization task involving shape optimization of rotor blades in turbo-machinery.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1995

A psychophysiological evaluation of the perceived urgency of auditory warning signals

One significant concern that pilots have about cockpit auditory warnings is that the signals presently used lack a sense of priority. The relationship between auditory warning sound parameters and perceived urgency is, therefore, an important topic of enquiry in aviation psychology. The present investigation examined the relationship among subjective assessments of urgency, reaction time, and brainwave activity with three auditory warning signals. Subjects performed a tracking task involving automated and manual conditions, and were presented with auditory warnings having various levels of perceived and situational urgency. Subjective assessments revealed that subjects were able to rank warnings on an urgency scale, but rankings were altered after warnings were mapped to a situational urgency scale. Reaction times differed between automated and manual tracking task conditions, and physiological data showed attentional differences in response to perceived and situational warning urgency levels. This study shows that the use of physiological measures sensitive to attention and arousal, in conjunction with behavioural and subjective measures, may lead to the design of auditory warnings that produce a sense of urgency in an operator that matches the urgency of the situation.

Sound↗

NASA NTRS2011

Integrating Machine Learning into a Crowdsourced Model for Earthquake-Induced Damage Assessment

On January 12th, 2010, a catastrophic 7.0M earthquake devastated the country of Haiti. In the aftermath of an earthquake, it is important to rapidly assess damaged areas in order to mobilize the appropriate resources. The Haiti damage assessment effort introduced a promising model that uses crowdsourcing to map damaged areas in freely available remotely-sensed data. This paper proposes the application of machine learning methods to improve this model. Specifically, we apply work on learning from multiple, imperfect experts to the assessment of volunteer reliability, and propose the use of image segmentation to automate the detection of damaged areas. We wrap both tasks in an active learning framework in order to shift volunteer effort from mapping a full catalog of images to the generation of high-quality training data. We hypothesize that the integration of machine learning into this model improves its reliability, maintains the speed of damage assessment, and allows the model to scale to higher data volumes.

crowdsourcing↗

NASA NTRSDate not supplied

Informing NLP Learning Tasks by Tracking User Features: An ASRS Use Case using Kaona

There has been growing interest in utilizing natural language processing (NLP) algorithms in Aviation Safety. This interest has extended to leveraging the decades of records publicly available on the Aviation Safety Reporting System (ASRS). While related literature has given more emphasis in lessons learned from the narratives, our prior work has focused on using NLP to support narrative search in the ASRS. Specifically, we evaluated if the use of alternative search mechanisms to keyword search, such as the retrieval of related narratives even without matching keywords could improve narrative discovery. A difficulty in experimenting alternative search mechanisms in any information retrieval task is the lack of ground truth. To address this limitation, we propose Kaona, a lightweight interface which enables the prototyping of alternative search retrieval tasks, by tracking user experience both explicitly (user-specified feedback), or implicitly (user navigation through interface affordances). Differently from distracting requests for feedback during user navigation, Kaona collects explicit feedback from users by mapping them to affordances which support the user workflow, while obtaining ground truth information for learning tasks.

human-computer-interaction↗

DOE OSTI2021

Neural networks to learn protein sequence–function relationships from deep mutational scanning data

Understanding the relationship between protein sequence and function is necessary to design new and useful proteins with applications in bioenergy, medicine, and agriculture. The mapping from sequence to function is tremendously complex because it involves thousands of molecular interactions that are coupled over multiple lengths and timescales. We show that neural networks can learn the sequence–function mapping from large protein datasets. Neural networks are appealing for this task because they can learn complicated relationships from data, make few assumptions about the nature of the sequence–function relationship, and can learn general rules that apply across the length of the protein sequence. We demonstrate that learned models can be applied to design new proteins with properties that exceed natural sequences.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Cybersecurity Workforce Training for SMR Integration into Distribution Grids: A Competency Framework and Containerized Hands-On Lab for the SMR/DER/Microgrid Boundary

Small modular reactors (SMRs) and microreactors are entering the U.S. distribution grid as synchronous generation on feeders designed for loads and inverter-based distributed energy resources (DERs). No existing cybersecurity training program addresses this intersection of nuclear operations, DER management, and operational technology security. As subcontractor to Iowa State University on the CyDERMS Center, Argonne analyzed the relevant standards and training landscape, translated the resulting gaps into a twelve-objective competency framework across distribution-operator and graduate-analyst role tracks, and built a containerized training lab using a ∼400-bus composite grid model behind a realistically simulated Modbus TCP SCADA stack. The analysis isolates the balance-of-plant / energy-management-system (BOP/EMS) boundary as the critical jurisdictional seam where, as of March 2026, neither NRC nor NERC CIP cleanly claims cybersecurity responsibility for distribution-connected SMRs. The framework maps each objective across NIST CSF 2.0, ISA/IEC 62443, NIST NICE Task–Knowledge–Skill statements, and NRC RG 5.71 awareness-and-training controls. The training lab implements operator-recognition assessment scenarios spanning grid-side disturbances and telemetry-layer anomalies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1979

Western energy related overhead monitoring project. Phase 2: Summary

Assistance by NASA to EPA in the establishment and maintenance of a fully operational energy-related monitoring system included: (1) regional analysis applications based on LANDSAT and auxiliary data; (2) development of techniques for using aircraft MSS data to rapidly monitor site specific surface coal mine activities; and (3) registration of aircraft MSS data to a map base. The coal strip mines used in the site specific task were in Campbell County, Wyoming; Big Horn County, Montana; and the Navajo mine in San Juan County, New Mexico. The procedures and software used to accomplish these tasks are described.

Anderson, J. E.↗

NASA NTRS1982

SEPAC flight software detailed design specifications, volume 1

The detailed design specifications (as built) for the SEPAC Flight Software are defined. The design includes a description of the total software system and of each individual module within the system. The design specifications describe the decomposition of the software system into its major components. The system structure is expressed in the following forms: the control-flow hierarchy of the system, the data-flow structure of the system, the task hierarchy, the memory structure, and the software to hardware configuration mapping. The component design description includes details on the following elements: register conventions, module (subroutines) invocaton, module functions, interrupt servicing, data definitions, and database structure.

Source record↗

NASA NTRS1996

Studies of Westward Electrojets and Field-Aligned Currents in the Magnetotail During Substorms: Implications for Magnetic Field Models

This section outlines those tasks undertaken in the final year that contribute integrally to the overarching project goals. Fast, during the final year, it is important to note that the project benefited greatly with the addition of a Boston University graduate student, Ms. Karen Hirsch. Jointly, we made substantial progress on the development of and improvements to magnetotail magnetic field and plasma models. The ultimate aim of this specific task was to assess critically the utility of such models for mapping low-altitude phenomena into the magnetotail (and vice-versa). The bulk of this effort centered around the finite-width- magnetotail convection model developed by and described by Spence and Kivelson (J. Geophys. Res., 98, 15,487, 1993). This analytic, theoretical model specifies the bulk plasma characteristics of the magnetotail plasma sheet (number density, temperature, pressure) across the full width of the tail from the inner edge of the plasma sheet to lunar distances. Model outputs are specified by boundary conditions of the source particle populations as well as the magnetic and electric field configuration. During the reporting period, we modified this code such that it can be interfaced with the auroral particle precipitation model developed by Dr. Terry Onsager. Together, our models provide a simple analytic specification of the equatorial distribution of fields and plasma along with their low-altitude consequences. Specifically, we have built a simple, yet powerful tool which allows us to indirectly 'map' auroral precipitation signatures (VDIS, inverted-V's, etc.) measured by polar orbiting spacecraft in the ionosphere, to the magnetospheric equatorial plane. The combined models allow us to associate latitudinal gradients measured in the ion energy fluxes at low-altitudes with the large-scale pressure gradients in the equatorial plane. Given this global, quasi-static association, we can then make fairly strong statements regarding the location of discrete features in the context of the global picture. We reported on our initial study at national and international meetings and published the results of our predictions of the low-altitude signatures of the plasma sheet. In addition, the PI was invited to contribute a publication to the so-called 'Great Debate in Space Physics' series that is a feature of EOS. The topic was on the nature of magnetospheric substorms. Specific questions of the when and where a substorm occurs and the connection between the auroral and magnetospheric components were discussed in that paper. This paper therefore was derived exclusively from the research supported by this grant. Attachment: Empirical modeling of the quite time nightside magnetosphere.' 'CRRES observations of particle flux dropout event.' The what, where, when, and why of magnetospheric substorm triggers'. and 'Low altitude signature of the plasma sheet: model prediction of local time dependence'.

Spence, Harlan E.↗

NASA NTRS1994

Earth Observation

For pipeline companies, mapping, facilities inventory, pipe inspections, environmental reporting, etc. is a monumental task. An Automated Mapping/Facilities Management/Geographic Information Systems (AM/FM/GIS) is the solution. However, this is costly and time consuming. James W. Sewall Company, an AM/FM/GIS consulting firm proposed an EOCAP project to Stennis Space Center (SSC) to develop a computerized system for storage and retrieval of digital aerial photography. This would provide its customer, Algonquin Gas Transmission Company, with an accurate inventory of rights-of-way locations and pipeline surroundings. The project took four years to complete and an important byproduct was SSC's Digital Aerial Rights-of-Way Monitoring System (DARMS). DARMS saves substantial time and money. EOCAP enabled Sewall to develop new products and expand its customer base. Algonquin now manages regulatory requirements more efficiently and accurately. EOCAP provides government co-funding to encourage private investment in and broader use of NASA remote sensing technology. Because changes on Earth's surface are accelerating, planners and resource managers must assess the consequences of change as quickly and accurately as possible. Pacific Meridian Resources and NASA's Stennis Space Center (SSC) developed a system for monitoring changes in land cover and use, which incorporated the latest change detection technologies. The goal of this EOCAP project was to tailor existing technologies to a system that could be commercialized. Landsat imagery enabled Pacific Meridian to identify areas that had sustained substantial vegetation loss. The project was successful and Pacific Meridian's annual revenues have substantially increased. EOCAP provides government co-funding to encourage private investment in and broader use of NASA remote sensing technology.

Source record↗

DOE OSTI2020

System and method for generation of event driven, tuple-space based programs

In a system for automatic generation of event-driven, tuple-space based programs from a sequential specification, a hierarchical mapping solution can target different runtimes relying on event-driven tasks (EDTs). The solution uses loop types to encode short, transitive relations among EDTs that can be evaluated efficiently at runtime. Specifically, permutable loops translate immediately into conservative point-to-point synchronizations of distance one. A runtime-agnostic which can be used to target the transformed code to different runtimes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

System and method for generation of event driven, tuple-space based programs

Baskaran, Muthu M.↗