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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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NASA NTRS2024

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗

NASA NTRS2024

Acquisition of and Access to Research Omics Data

Omics data are essential for understanding the myriad and complex effects of space environments on humans. To assure maximum benefit from these kinds of data, the NASA Human Research Program Data Management Plan stipulates that human omics data should be archived within and accessed through the NASA Life Sciences Portal (NLSP). The NLSP has the capability to acquire and provision access to omics (and other kinds of) research results for individual and ad-hoc groups of subjects at the direction of institutional review boards, or other authorizing bodies or individuals, per institutional, program and investigation-specific policies and procedures. However, because some single-subject omics data, like CT scans and other kinds of large, complex biomedical data, could be used to identify heretofore unknown risks to the subject’s health, or, in certain cases, be used to identify a subject, NASA Policy Directive 7170.1 describes various policies regarding the management of and access to “research genetic testing” data, which includes many kinds of omics data. For example, NPD 7170.1 prohibits access to human research genetic data by NASA personnel who make employment decisions for the subjects from whom the data were obtained. To meet the objective of acquiring research omics data for NLSP in compliance with the policies in NPD 7170.1 and other applicable NASA policies, we designed NOMADS (the NLSP Omics Multimodal Acquisition of Data System), a new component that supports the transfer of large research data files, including research genetic testing data, using one of several different transfer mechanisms. The choice of mechanism is made by the submitter of the data, with guiding information from the system, and is likely to often be determined in large part by the nature and source location of the data. For example, for small files where the source data files are not already stored in a cloud storage system, users are likely to prefer to transfer their data to the NLSP via a web browser. Conversely, for large sets of files already organized and stored in a cloud storage system, users may opt for NOMAD’s cloud-to-cloud transfer method. All omics datasets targeted for the NASA Life Sciences Data Archive must pass a variety of quality checks to ensure data integrity and adherence to the standards defined by the LSDA Data Submission Guidelines (DSG) (see https://nlsp.nasa.gov/explore/lsdahome/datasubmit). These include requirements that data are consistent with open standards established by the omics community. Non-compliant data will not be accepted however archivists are available to advise submitters on how to revise data submissions and re-submit until compliance is achieved. Following compliance with the LSDA DSG, omics data next undergo a variety of additional quality checks to ensure the data meet omics community standards. Domain specific Omics data quality control tools and techniques are continually evolving and linked to the advancements in omics assays utilized and thus, the tools and techniques utilized by the LSDA for data quality control and validation will need to be sustained accordingly. All human omics data will be access controlled according to the policies described above, and requiring IRB approval for any additional access grants once the data are acquired (including access for analysis using the NLSP workspace tools).

Omics↗

NASA NTRS2002

Achievements of the DOT-NASA Joint Program on Remote Sensing and Spatial Information Technologies: Application to Multimodal Transportation

This report presents three-year accomplishments from the national program on Commercial Remote Sensing and Geospatial Technology (CRSGT) application to transportation, administered by the U.S. Department of Transportation (U.S. DOT) in collaboration with the National Aeronautics and Space Administration (NASA). The joint program was authorized under Section 5113 of the Transportation Equity Act for the 21st Century (TEA-21). This is the first national program of its type focusing on transportation applications of emerging commercial remote sensing technologies. U.S. DOT's Research and Special Programs Administration manages the program in coordination with NASA's Earth Science Enterprise's application programs. The program focuses on applications of CRSGT products and systems for providing smarter and more efficient transportation operations and services. The program is performed in partnership with four major National Consortia for Remote Sensing in Transportation (NCRST). Each consortium focuses on research and development of products in one of the four priority areas for transportation application, and includes technical application and demonstration projects carried out in partnership with industries and service providers in their respective areas. The report identifies products and accomplishments from each of the four consortia in meeting the goal of providing smarter and more efficient transportation services. The products and results emerging from the program are being implemented in transportation operations and services through state and local agencies. The Environmental Assessment and Application Consortium (NCRST-E) provides leadership for developing and deploying cost effective environmental and transportation planning services, and integrates CRSGT advances for achieving smarter and cost effective corridor planning. The Infrastructure Management Consortium (NCRST-I) provides leadership in technologies that achieve smarter and cheaper ways of managing transportation infrastructure assets, operation, and inspection, and integrates CRSGT advances for achieving infrastructure security. The Traffic Flow Consortium (NCRST-F) provides leadership to develop new tools for regional traffic flow management including heavy vehicles and intermodal flow of freight, and integrates CRSGT advances for complementing and extending the reach of ITS user services. The Safety, Hazards and Disasters (NCRST-H) provides leadership for deploying remote sensing technology to locate transportation hazards and improve disaster recovery, and integrates CRSGT advances for application to protect transportation systems from terrorism. The DOT-NASA team is proud to present this report of accomplishments on products and results emerging from the joint program for application to transportation practice.

Source record↗

NASA NTRS2013

Micro-Spec: An Ultra-Compact, High-Sensitivity Spectrometer for Far-Infrared and Sub-Millimeter Astronomy

High-performance, integrated spectrometers operating in the far-infrared and sub-millimeter promise to be powerful tools for the exploration of the epochs of reionization and initial galaxy formation. These devices, using high-efficiency superconducting transmission lines, can achieve the performance of a meter-scale grating spectrometer in an instrument implemented on a four-inch silicon wafer. Such a device, when combined with a cryogenic telescope in space, provides an enabling capability for studies of the early universe. Here, the optical design process for Micro-Spec (mu-Spec) is presented, with particular attention given to its two-dimensional diffractive region, where the light of different wavelengths is focused on the different detectors. The method is based on the stigmatization and minimization of the light path function in this bounded region, which results in an optimized geometrical configuration. A point design with an efficiency of approx. 90% has been developed for initial demonstration, and can serve as the basis for future instruments. Design variations on this implementation are also discussed, which can lead to lower efficiencies due to diffractive losses in the multimode region.

spectroscopic instrumentation↗