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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 793 records · Page 44

Functional Mock-up Interface - Machine Learning Center (FMI-MLC) v1

The Functional Mock-up Interface - Machine Learning Center is a tool to interface the Python-Tensorflow library with building simulation models, to develop and train machine learning-based controls. In particular, this framework allows the use of reinforcement learning through the standardized Functional Mock-up Interface, an open industry standard for co-simulation. First application was the development of a controller for dynamic façade and heating ventilation and air conditioning (HVAC) systems.

Gehbauer, Christoph↗

Inl Open Ondemand Applications

Open OnDemand is a software tool that is used to access HPC resources. It provides a framework for organizations to create apps and other additional functionality that may be useful to the organization. This code expands upon the pre-existing INL applications, including the NEAMS Workbench application, MOOSE Herd applications, and others. These changes significantly expand upon the functionality originally provided. Due to the extensive functionality that we added, these changes would not be added to the original application but would function as a standalone application that other organizations would be able to utilize on their own systems.

Biggs, BrandonS.↗

Inl Open Ondemand Dashboard Applications

Open OnDemand is a software tool that is used to access HPC resources. It provides a framework for organizations to create apps and other additional functionality that may be useful to the organization. This code creates new INL applications. These changes significantly expand upon the functionality originally provided. Due to the extensive functionality that we added, these changes would not be added to the original application but would function as additional applications that other organizations would be able to utilize on their own systems.

Biggs, Brandon [Idaho National Laboratory (INL), I↗

Lighting Control in Patient Rooms: Understanding Nurses’ Perceptions of Hospital Lighting Using Qualitative Methods

Here, this study differs in its methodological approach from previously published research by interpreting qualitative results against existing literature to understand how nurses conceptualize medical–surgical patient rooms as productive settings in relation to lighting, as well as the ways in which nurses believe these spaces could be enhanced for patient satisfaction. Content analysis was used to interpret themes emerging from nurses’ subjective responses to open-ended items. Three of the facilities had older, traditional lighting systems; one had a contemporary framework. A theme of environmental control over both overhead and task lighting emerged from data from all items. Although controllability was among the “best” lighting attributes, more refinement is necessary for optimal staff productivity and patient satisfaction. Daylighting was also considered to be among the best attributes. Control over light level via additional dimming capability for patients, as well as additional light sources, was prominent across the four hospitals. Unique to the more modern facility, trespassing of light was problematic for nurses considering the experiences of patients—even where modern models exist, more attention can be paid to the ways in which window shades, and light sources outside of rooms, penetrate spaces and affect users. Finally, the finding that nurses and patients desire greater control over the lighting in patient rooms is consistent with Ulrich’s theory of supportive design for healthcare and coincides with advances in lighting technology. Despite differences in the level of sophistication in lighting among the four facilities, control continues to be a primary concern for nurses.

60 APPLIED LIFE SCIENCES↗

PIPER: Performance Insight for Programmers and Exascale Runtimes (Final Technical Report)

This project concentrated on the development of novel performance tools and analysis techniques for large scale parallel systems and applications, eventually targeting exascale platforms. Activities conducted included work to novel root cause detection approaches and an auto-tuning framework for parallel systems. The work has led to several software solutions, which are available as open source.

97 MATHEMATICS AND COMPUTING↗

The Civil Aviation Sector in Lebanon: Institutional Reforms - Part 1

Civil aviation is one of the key contributors to a successful economic system. This has been recognized within Lebanon, which is undertaking developing a new civil aviation strategy encompassing a program of organizational reform, coordinated internationally, to meet the challenges of the new century. Such strategy is vital, as it will provide a coherent vision for the sector, compliment the extensive investments deployed by Lebanon in its aviation infrastructure, and guide future planning and investments. The proposed Civil Aviation Strategy for Lebanon has two major components: (1) institutional reform aiming at creating effective overall legal and regulatory frameworks in-line with current international best practice; and (2) implementation of liberalization measures and open skies policy. This paper aims to: (1) present Lebanon's current institutional arrangements; (2) review the institutional arrangements in key select countries (in order to define current trends in best institutional practice); (3) discuss the proposed institutional reform (which are at the basis of Lebanon's Draft Civil Aviation Reform Law) while showing that they conform with the identified best institutional trends; and (4) outline an implementation plan. The Draft Law has been approved by the Council of Ministers and now awaits Parliamentary endorsement.

Baaj, M. Hadi↗

New developments in space radiation research at NASA: Annotating data using a novel radiation biology ontology

Like many interdisciplinary sciences, data producers and consumers in the field of radiation biology often use a wide variety of terminology to describe their experiments and data. Furthermore, space systems and technologies are rapidly evolving, and a shared understanding and common terminology for these is also lacking. The efficiency of research organizations can be enhanced by standardizing metadata through the use of knowledge resources like ontologies. Employing a sophisticated model such as a formal ontology to standardize metadata enables automated data acquisition processes and supports more complete, accurate meta-analysis through more efficient and complete data discovery and retrieval, particularly when using multiple data sources. Thus, we developed the Radiation Biology Ontology (RBO) in order to improved radiation biology metadata uniformity and transparency. We used open-source software (the Ontology Development Kit, Protégé and WebProtégé) and worked within the OBO Foundry framework, which includes a set of ontology development principles and practices for ontology consistency, uniformity, and accountability. The RBO has now been incorporated into two radiation research data repositories, NASA’s GeneLab omics database (https://genelab.nasa.gov), and the European Commission STORE database (https://www.storedb.org/). Continuous build integration tools allowed our international RBO collaboration to be more efficient and focus its efforts on semantic model design. Currently, the RBO contains over 300 annotated classes and individuals specific to the study of radiation on biological systems, as well as imports of many additional classes from other OBO Foundry ontologies that relate to and/or provide context for these RBO entities. We publish the RBO through the OBO Foundry, so that it is available for browsing, download, and querying through NCBI Bioportal web site and application programming interface. The NASA Ames Life Science Data Archive (ALSDA) is also in the process of adopting use of the RBO, taking NASA one step closer to a knowledge-based system for space biology data. It is our hope that the global communities of radiation research Investigators, data curators and data analysts can similarly leverage the RBO and will contribute to its further development.

radiation↗

Reproducibility in materials informatics: lessons from ‘A general-purpose machine learning framework for predicting properties of inorganic materials’

The integration of machine learning techniques in materials discovery has become prominent in materials science research and has been accompanied by an increasing trend towards open data and open-source tools to propel the field. Despite the increasing usefulness and capabilities of these tools, developers neglecting to follow reproducible practices presents a significant barrier for other researchers looking to use or build upon their work. In this study, we investigate the challenges encountered while attempting to reproduce a section of the results presented in “A general-purpose machine learning framework for predicting properties of inorganic materials.” Our analysis identifies four major categories of challenges: (1) reporting software dependencies, (2) recording and sharing version logs, (3) sequential code organization, and (4) clarifying code references within the manuscript. The result is a proposed set of tangible action items for those aiming to make material informatics tools accessible to, and useful for the community.

36 MATERIALS SCIENCE↗

Implementation of fuel management multi-cycle optimization capabilities in RAVEN optimization framework

Optimization in nuclear fuel-management assists the core reload engineer with finding optimal out-of-core and in-core strategies. RAVEN is INL’s open source software that is equipped with fuel-management optimization capabilities including single-cycle, single- and multi-objective optimization of pressurized water reactors (PWRs) loading patterns (LP) of a fresh core using genetic algorithm (GA) and non-dominated sorting genetic algorithm (NSGA-II). In practice, however, medium and long term planning of fuel-management needs a multi-cycle approach, where the history and availability of fuel assemblies is considered in the optimization process. In this paper, we present a description of an initial expansion of RAVEN fuel-management optimization capabilities for a multi-cycle optimization framework. N-th cycle optimization capabilities that account for the unique history of recycled fuel assembly in the core were added. The multi-cycle optimization approach taken is formulated as a cycle-wise optimization problem where out-of-core decisions are used to onset each cycle optimization. Out-of-core decisions are managed externally to the in-core optimization by a fuel inventory management module. A proof-of-concept optimization problem is also presented.

42 - ENGINEERING↗

Future Standardization of Space Telecommunications Radio System with Core Flight System

NASA Glenn Research Center (GRC) is integrating the NASA Space Telecommunications Radio System (STRS) Standard with the Core Flight System (cFS). The STRS standard provides a common, consistent framework to develop, qualify, operate and maintain complex, reconfigurable and reprogrammable radio systems. The cFS is a flexible, open architecture that features a plug-and-play software executive called the Core Flight Executive (cFE), a reusable library of software components for flight and space missions and an integrated tool suite. Together, STRS and cFS create a development environment that allows for STRS compliant applications to reference the STRS APIs through the cFS infrastructure. These APis are used to standardize the communication protocols on NASAs space SDRs. The cFE-STRS Operating Environment (OE) is a portable cFS library, which adds the ability to run STRS applications on existing cFS platforms. The purpose of this paper is to discuss the cFE-STRS OE prototype, preliminary experimental results performed using the Advanced Space Radio Platform (ASRP), the GRC Sband Ground Station and the SCaN (Space Communication and Navigation) Testbed currently flying onboard the International Space Station. Additionally, this paper presents a demonstration of the Consultative Committee for Space Data Systems (CCSDS) Spacecraft Onboard Interface Services (SOIS) using electronic data sheets inside cFE. This configuration allows for the data sheets to specify binary formats for data exchange between STRS applications. The integration of STRS with cFS leverages mission-proven platform functions and mitigates barriers to integration with future missions. This reduces flight software development time and the costs of software-defined radio (SDR) platforms. Furthermore, the combined benefits of STRS standardization with the flexibility of cFS provide an effective, reliable and modular framework to minimize software development efforts for spaceflight missions.

space communications↗

Future Standardization of Space Telecommunications Radio System with Core Flight System

NASA Glenn Research Center (GRC) is integrating the NASA Space Telecommunications Radio System (STRS) Standard with the Core Flight System (cFS), an avionics software operating environment. The STRS standard provides a common, consistent framework to develop, qualify, operate and maintain complex, reconfigurable and reprogrammable radio systems. The cFS is a flexible, open architecture that features a plugand- play software executive called the Core Flight Executive (cFE), a reusable library of software components for flight and space missions and an integrated tool suite. Together, STRS and cFS create a development environment that allows for STRS compliant applications to reference the STRS application programmer interfaces (APIs) that use the cFS infrastructure. These APIs are used to standardize the communication protocols on NASAs space SDRs. The cFS-STRS Operating Environment (OE) is a portable cFS library, which adds the ability to run STRS applications on existing cFS platforms. The purpose of this paper is to discuss the cFS-STRS OE prototype, preliminary experimental results performed using the Advanced Space Radio Platform (ASRP), the GRC S‑ band Ground Station and the SCaN (Space Communication and Navigation) Testbed currently flying onboard the International Space Station (ISS). Additionally, this paper presents a demonstration of the Consultative Committee for Space Data Systems (CCSDS) Spacecraft Onboard Interface Services (SOIS) using electronic data sheets (EDS) inside cFE. This configuration allows for the data sheets to specify binary formats for data exchange between STRS applications. The integration of STRS with cFS leverages mission-proven platform functions and mitigates barriers to integration with future missions. This reduces flight software development time and the costs of software-defined radio (SDR) platforms. Furthermore, the combined benefits of STRS standardization with the flexibility of cFS provide an effective, reliable and modular framework to minimize software development efforts for spaceflight missions.

space communications↗

Porous Ti-MOF-74 Framework as a Strong-Binding Nitric Oxide Scavenger

Combining synthesis, infrared spectroscopy, and ab initio modeling we show that the titanium-based porous framework Ti-MOF-74 has potential as an environmental nitric oxide (NO) scavenger, exhibiting an extraordinarily strong binding affinity and selectivity over other flue-gas components. The robustness upon exposure to water vapor and high flue-gas stack temperatures suggests that this material can perform well in an industrial environment. In-depth analysis of the Ti-NO bond indicates that the NO forms a strong covalent bond with the Ti. The process of this NO bond formation involves a reaction with the OH- capping groups of the Ti to form NO x groups, after which the excess NO binds to the open Ti metal sites. Ti-MOF-74 thus becomes, to the best of our knowledge, the first known porous framework that binds NO significantly stronger than water, providing novel avenues for environmental and physiological scavenging applications.

36 MATERIALS SCIENCE↗

Interactive web mapping tools and custom subsurface cross-sections for interdisciplinary geologic investigation

Using Python-based geospatial analytics, open-source web mapping technologies, geophysical data models, and subsurface stratigraphy models from the Regional Geology Geologic Framework Model database assembled by Los Alamos National Laboratory, we developed a suite of web-based geologic investigation tools to identify and understand subsurface structures and geophysical properties concerning salt and shale formations within the contiguous United States. Coupled with a web map interface, these tools allow for the interactive visualization of various geologic data and demonstrate the ability to quickly generate custom subsurface cross-sections, borehole charts, and diagrams for azimuthal orientation data. These capabilities were developed for stakeholder and researcher use to facilitate informed decision making for spent nuclear waste disposition. However, these capabilities provide a flexible model for a variety of subsurface investigation needs, and we have demonstrated this flexibility by adapting these tools to meet visualization needs for various subsurface models within a web-based platform.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Quantum dynamics of non-Hermitian many-body Landau-Zener systems

Here, we develop a framework to solve a large class of linearly driven non-Hermitian quantum systems. Such a class of models in the Hermitian scenario is commonly known as multistate Landau-Zener models. The non-Hermiticity is due to the anti-Hermitian couplings between the diabatic levels. We find that there exists a conservation law, unique to this class of models, that describes the simultaneous growth of the unnormalized wave functions. These models have practical applications in Bose-Einstein condensates, and they can describe the dynamics of multispecies bosonic systems. The conservation law relates to a pair-production mechanism that explains the dissociation of diatomic molecules into atoms. We provide a general framework for both solvable and semiclassically solvable non-Hermitian Landau-Zener models. Our findings will open alternative avenues for a number of diverse emergent phenomena in explicitly time-dependent non-Hermitian quantum systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Bridging Python to Silicon: The SODA Toolchain

Systems performing scientific computing, data analysis, and machine learning tasks have a growing demand for application-specific accelerators that can provide high computational performance while meeting strict size and power requirements. However, the algorithms and applications that need to be accelerated are evolving at a rate that is incompatible with manual design processes based on hardware description languages. Agile hardware design tools based on compiler techniques can help by quickly producing an application-specific integrated circuit (ASIC) accelerator starting from a high-level algorithmic description. Here, we present the software-defined accelerator (SODA) synthesizer, a modular and open-source hardware compiler that provides automated end-to-end synthesis from high-level software frameworks to ASIC implementation, relying on multilevel representations to progressively lower and optimize the input code. Our approach does not require the application developer to write any register-transfer level code, and it is able to reach up to 364 giga floating point operations per second (GFLOPS)/W efficiency (32-bit precision) on typical convolutional neural network operators.

97 MATHEMATICS AND COMPUTING↗

Reconfigurable Intelligent Surfaces in Action for Nonterrestrial Networks

Next-generation communication technology will be made possible by cooperation between terrestrial networks with nonterrestrial networks (NTNs) composed of high-altitude platform stations (HAPSs) and satellites. Further, as humanity embarks on the long road to establish new habitats on other planets, the cooperation between NTNs and deep-space networks (DSNs) will be necessary. In this regard, we propose the use of reconfigurable intelligent surfaces (RISs) to improve coordination between these networks given that RISs perfectly match the size, weight, and power (SWaP) restrictions of operating in space. Here, a comprehensive framework of RIS-assisted nonterrestrial and interplanetary communications is presented that pinpoints challenges, use cases, and open issues. Furthermore, the performance of RIS-assisted NTNs under environmental effects, such as solar scintillation and satellite drag, is discussed in light of simulation results.

42 ENGINEERING↗

Enabling Pulse-level Programming, Compilation, and Execution in XACC

Noisy gate-model quantum processing units (QPUs) are currently available from vendors over the cloud, and digital quantum programming approaches exist to run low-depth circuits on physical hardware. These digital representations are ultimately lowered to pulse-level instructions by vendor quantum control systems to affect unitary evolution representative of the submitted digital circuit. Vendors are beginning to open this pulse-level control system to the public via specified interfaces. Robust programming methodologies, software frameworks, and backend simulation technologies for this analog model of quantum computation will prove critical to advancing pulse-level control research and development. Prototypical use cases for this include error mitigation, optimal pulse control, and physics-inspired pulse construction. Here we present an extension to the XACC quantum-classical software framework that enables pulse-level programming for superconducting, gate-model quantum computers, and a novel, general, and extensible pulse-level simulation backend for XACC that scales on classical compute clusters via MPI. Our work enables custom backend Hamiltonian definitions and gate-level compilation to available pulses with a focus on performance and scalability. We end with a demonstration of this capability, and show how to use XACC for pertinent pulse-level programming tasks.

97 MATHEMATICS AND COMPUTING↗

Understanding and Improving Energy Efficiency of Regional Mobility Systems Leveraging System-Level Data

Increased congestion required urban Americans to travel 6.8 billion hours more and purchase 3.1 billion gallons of fuel for a congestion cost of $\$$153 billion, according to the 2019 Urban Mobility Report. How to effectively manage the regional mobility system and improve the energy efficiency presents a big challenge to public agencies. Recent years have witnessed massive multi-jurisdictional multi-modal system-level data from various sources, which provides an unprecedented opportunity to improve the mobility system and its energy efficiency. However, implications of system-level data for mobility and energy efficiency are unclear. Those system-level data sets are siloed, spatially and temporally sparse, biased, not unified, and lacking of insights for system management. Consequently, there is a real need to acquire, fuse, mine and learn from multi-source system-level data to prepare public agencies to deal more effectively with large-scale energy efficiency modeling, management and planning. This project proposes to intensively review inexpensive, replicable and openly-accessible data from multi-modal systems, develop a data-driven system-level modeling framework enabled and validated by data, identify the energy inefficiencies of mobility systems from infrastructure, vehicles, passenger systems, and quantify the benefits of system-level strategies to improve mobility/energy efficiency. In addition, this research develops models to effectively estimate energy consumption and emissions from various types of vehicles on the roadway networks, with high granularity and high fidelity. Traditional models often heavily rely on aggregated infrastructure or vehicle/passenger data, for example, the census survey, land-use, and traffic counts of one or several classes, which may lead to research gaps considering the emerging vehicle technologies. Those models do not contain individual vehicular information. We propose an integrated data-driven method that combines multiple network modeling components, featuring the utilization of state-wide vehicle registration data. The additional vehicle registration data improve the model performance, and produce high-resolution vehicle-specific estimates of emissions and network performance metrics. Two case studies on the Pittsburgh and Philadelphia regional network show that the proposed method can efficiently and effectively estimate the emissions of a large-scale network, and provide valuable information for evaluating common management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗