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At least 235 records · Page 13

Capabilities of the Materials Contamination Team at Marshall Space Flight Center

The Materials Contamination Team at the Marshall Space Flight Center (MSFC) has been recognized for its contributions supporting the National Aeronautics and Space Administration (NASA) spacecraft development programs. These programs include the Reusable Solid Rocket Motor (RSRM), Chandra X-Ray Observatory, and the International Space Station (ISS). The Environmental Effects Group, with the Materials Contamination Team and the Space Environmental Effects Team has been an integral part of NASA's success by the testing, evaluation, and qualification of materials, hardware, and processes. This paper focuses on the capabilities of the Materials Contamination Team. The Materials Contamination Team's realm of responsibility includes establishing contamination control during all phases of hardware development, including design, manufacturing, assembly, test, transportation, launch site processing, on-orbit exposure, return, and refurbishment. The team continues its mission of reducing the risk of equipment failure due to molecular or particulate contamination. Contamination is a concern in the Space Shuttle with sensitive bond-lines and reactive fluid (liquid oxygen) compatibility as well as for spacecraft with sensitive optics, such as Hubble Space Telescope and Chandra X-ray Observatory. The Materials Contamination Team has a variety of facilities and instrumentation capable of contaminant detection, identification, and monitoring. The team addresses material applications dealing with environments, including production facilities, clean rooms, and on-orbit exposure. The optically stimulated electron emission (OSEE) system, the Ultraviolet (UV) fluorescence (UVF) surface contamination detection, and the Surface Optics Corporation 400 (SOC 400) portable hand-held Fourier Transform Infrared (FTIR) spectrometer are state-of-the-art tools for in-process molecular contamination detection. The team of engineers and technicians also develop contamination calibration standards and evaluate new surface cleanliness inspection technologies. The team utilizes facilities for on-orbit simulation testing of materials for outgassing and molecular film deposition characteristics in the presence of space environmental effects, such as Atomic Oxygen (AO) and UV radiation exposure. The Materials Contamination Team maintains databases for process materials as well as outgassing and optical compatibility test results for specific environments.

Burns, Howard↗

NASA Tech Briefs, April 2006

The topics covered include: 1) Replaceable Sensor System for Bioreactor Monitoring; 2) Unitary Shaft-Angle and Shaft-Speed Sensor Assemblies; 3) Arrays of Nano Tunnel Junctions as Infrared Image Sensors; 4) Catalytic-Metal/PdO(sub x)/SiC Schottky-Diode Gas Sensors; 5) Compact, Precise Inertial Rotation Sensors for Spacecraft; 6) Universal Controller for Spacecraft Mechanisms; 7) The Flostation - an Immersive Cyberspace System; 8) Algorithm for Aligning an Array of Receiving Radio Antennas; 9) Single-Chip T/R Module for 1.2 GHz; 10) Quantum Entanglement Molecular Absorption Spectrum Simulator; 11) FuzzObserver; 12) Internet Distribution of Spacecraft Telemetry Data; 13) Semi-Automated Identification of Rocks in Images; 14) Pattern-Recognition Algorithm for Locking Laser Frequency; 15) Designing Cure Cycles for Matrix/Fiber Composite Parts; 16) Controlling Herds of Cooperative Robots; 17) Modification of a Limbed Robot to Favor Climbing; 18) Vacuum-Assisted, Constant-Force Exercise Device; 19) Production of Tuber-Inducing Factor; 20) Quantum-Dot Laser for Wavelengths of 1.8 to 2.3 micron; 21) Tunable Filter Made From Three Coupled WGM Resonators; and 22) Dynamic Pupil Masking for Phasing Telescope Mirror Segments.

Source record↗

Using active learning to improve quasar identification for the DESI spectra processing pipeline

The Dark Energy Spectroscopic Instrument (DESI) survey uses an automatic spectral classification pipeline to classify spectra. QuasarNET is a convolutional neural network used as part of this pipeline originally trained using data from the Baryon Oscillation Spectroscopic Survey (BOSS). In this paper we implement an active learning algorithm to optimally select spectra to use for training a new version of the QuasarNET weights file using only DESI data, with the goal of improving classification accuracy. This active learning algorithm includes a novel outlier rejection step using a Self-Organizing Map to ensure we label spectra representative of the larger quasar sample observed in DESI. We perform two iterations of the active learning pipeline, assembling a final dataset of 5600 labeled spectra, a small subset of the approximately 1.3 million quasar targets in DESI's Data Release 1. When splitting the spectra into training and validation subsets we achieve similar performance to the previously trained weights file in completeness and purity calculated on the validation dataset but do so with less than one tenth of the amount of training data. The new weights also more consistently classify objects in the same way when used on unlabeled data compared to the old weights file. In the process of improving QuasarNET's classification accuracy we discovered a systemic error in QuasarNET's redshift estimation and used our findings to improve our understanding of QuasarNET's redshifts.

Machine learning↗

Identification of key steps in the evolution of anaerobic methanotrophy in Candidatus Methanovorans (ANME-3) archaea

Despite their large environmental impact and multiple independent emergences, the processes leading to the evolution of anaerobic methanotrophic archaea (ANME) remain unclear. This work uses comparative metagenomics of a recently evolved but understudied ANME group, “Candidatus Methanovorans” (ANME-3), to identify evolutionary processes and innovations at work in ANME, which may be obscured in earlier evolved lineages. We identified horizontal transfer of hdrA homologs and convergent evolution in carbon and energy metabolic genes as potential early steps in Methanovorans evolution. We also identified the erosion of genes required for methylotrophic methanogenesis along with horizontal acquisition of multiheme cytochromes and other loci uniquely associated with ANME. The assembly and comparative analysis of multiple Methanovorans genomes offers important functional context for understanding the niche-defining metabolic differences between methane-oxidizing ANME and their methanogen relatives. Furthermore, this work illustrates the multiple evolutionary modes at play in the transition to a globally important metabolic niche.

59 BASIC BIOLOGICAL SCIENCES↗

Bioinformatics and 3D Structural Analysis of the Coronavirus Main Protease Active Site Diversity

Coronaviruses (Coronaviridae) such as SARS‐CoV‐2 (severe acute respiratory syndrome coronavirus) and MERS‐CoV (Middle East respiratory syndrome coronavirus) have been the source of recent outbreaks and global health concerns. While vaccines have been essential for controlling the SARS‐CoV‐2 (COVID‐19) pandemic, it is uncertain whether they will be effective against future coronavirus strains. Therefore, identification or design of a broad‐spectrum drug that targets highly conserved regions of the main protease of multiple coronavirus strains is essential in the long term. As part of a virtual summer research experience with the RCSB PDB, bioinformatics tools were employed to predict and construct 3D models of the coronavirus main protease (MPro) using SARS‐CoV‐2 as the template, with a focus on mutational trends and active sites. This study focused on the active sites of MPro, a cysteine protease essential for viral assembly and replication. Sequence alignments and structure modeling of MPro structures has identified conserved regions across multiple coronavirus strains. Inhibition of MPro halts coronavirus replication, making it an ideal drug target, and studies of MPro may foster and accelerate the discovery of high affinity broad‐spectrum drugs.

Wu Wu, Amy↗

Lucy L’Ralph In-Flight Calibration and Results at (152830) Dinkinesh

The L'Ralph instrument is a key component of NASA's Lucy mission, intended to provide spectral image data of multiple Jupiter Trojans. The instrument operates from ∼0.35 to 4 μm using two focal plane assemblies: a 350–950 nm multispectral imager, Multi-spectral Visible Imaging Camera (MVIC), and a 0.97–4 μm imaging spectrometer, Linear Etalon Imaging Spectral Array (LEISA). Instrument calibration was established through ground testing before launch and has been monitored during cruise utilizing internal calibration sources and stellar targets. In-flight data have shown that the instrument thermal performance is exceeding expectations, allowing for early updates to LEISA radiometric and pointing calibrations. MVIC radiometric performance remains stable more than 3 yr since launch. The serendipitous identification of a new flyby target, (152830) Dinkinesh, allowed testing of instrument performance and interleaved LEISA and MVIC acquisitions on an asteroid target. Both MVIC and LEISA obtained data of Dinkinesh and its moon, Selam, demonstrating that they show good spectral agreement with an S- or Sq-type asteroid, along with evidence of a 3 μm absorption feature.

Amy A Simon↗

A review of prefabricated overclad panels for building energy retrofits

Over 50% of existing buildings in the US were constructed before 1980 and lack modern, energy-efficient technologies. Despite the large number of old buildings, less than 2% of buildings are retrofitted each year with many of those retrofits consisting of small incremental improvements that often ignore the building envelope. The opaque building envelope affects 25% of building energy use equating to 10% of total US primary energy use. To meet decarbonization goals by 2035, the US must increase the rate of retrofit of existing building envelopes. The process of prefabrication is one potential opportunity to increase the rate of envelope retrofits and reduce costs. Prefabrication is the process of manufacturing construction components in a controlled environment before shipping them on-site to perform assembly of the construction. The process of prefabrication has been demonstrated to increase production efficiency, quality control, and rate of production. Prefabricated overclad panels, consisting of a cladding material and insulation designed to be installed over the existing envelope, have been successfully used to retrofit existing buildings in countries other than the US; however, the technology still has some barriers to major market adoption within the US. This paper will present a review of current implementations and demonstrations of prefabricated overclad panels. The review will include identification of panel types, materials, and applications and aims to identify barriers to retrofit market entry and widespread adoption.

Hayes, Nolan [ORNL] (ORCID:0000000332245718)↗

LeaPP: Learning Pathways to Polymorphs through Machine Learning Analysis of Atomic Trajectories

Understanding the mechanisms underlying crystal nucleation and growth is crucial for many technological applications. Due to the short length and time scales involved, crystal nucleation is often studied using molecular simulations. Most existing approaches to extract the nucleation mechanism from simulations focus on the analysis of static snapshots of the configurations, potentially overlooking subtle local fluctuations and the history of the particles involved in the formation of solid nuclei. Here, in this work, we propose a novel methodology called LeaPP that categorizes nucleation trajectories based on the temporal information of their constituent particles. We leverage the time evolution of the local environment of the crystallizing particles to encapsulate the relationship between the structure and dynamics and distinguish between different evolving particle paths. Identification of the distinct particle paths further enables characterizing the nucleation trajectories into different pathways. Collectively, LeaPP provides a more nuanced understanding of nucleation through an unsupervised approach with lesser dependence on traditional order parameters. Furthermore, the pathways identified by LeaPP are predictive of the resulting polymorph. We demonstrate LeaPP on three different systems─Lennard-Jones-like particles, Ni 3 Al, and water on surfaces. The general methodology underlying LeaPP─considering the time evolution of the building blocks─applies to a wide range of self-assembly problems.

36 MATERIALS SCIENCE↗

Advances in genetic tools for metabolic engineering of non-conventional yeasts

Non-conventional yeasts are emerging as powerful alternatives to Saccharomyces cerevisiae for metabolic engineering, owing to their innate stress tolerance, broad substrate utilization, and distinctive metabolic capabilities. These attributes position them as promising chassis for producing biofuels, pharmaceuticals, and specialty chemicals. This review synthesizes recent advances in genetic toolkits for four such species—Pichia kudriavzevii (Issatchenkia orientalis), Starmerella bombicola, Debaryomyces hansenii, and Pachysolen tannophilus—highlighting progress across plasmid architectures (episomal and integrative), identification of autonomously replicating sequences and centromeric elements, and the development of safe-harbor genomic loci. We summarize promoter and terminator libraries enabling tunable expression, the expansion of auxotrophic and antifungal selection markers with recycling strategies, and the rapid adaptation of CRISPR-based systems (Cas9 and Cas12a) with optimized guide RNA expression, multiplex editing, and approaches that enhance homologous recombination (e.g., KU70/80 disruption). We also review landing-pad platforms for modular, repeated integrations and transposon-based tools (e.g., piggyBac) that facilitate multigene pathway assembly. Collectively, these innovations are accelerating design-build-test-learn cycles and enabling precise, scalable engineering of non-conventional yeasts. Remaining challenges—including limited species-specific episomal systems, variable transformation efficiencies, genome-stability concerns, and alternative codon usage—define clear priorities for future toolkit development. Together, these advances and open needs chart a path toward robust, sustainable biomanufacturing using diverse non-conventional yeast chassis.

59 BASIC BIOLOGICAL SCIENCES↗

Multipurpose Hyperspectral Imaging System

A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral imaging with or without relative movement of the imaging system, and it can be used to scan a target of any size as long as the target can be imaged at the focal plane; for example, automated inspection of food items and identification of single-celled organisms. The spectral resolution of this system is greater than that of prior terrestrial multispectral imaging systems. Moreover, unlike prior high-spectral resolution airborne and spaceborne hyperspectral imaging systems, this system does not rely on relative movement of the target and the imaging system to sweep an imaging line across a scene. This compact system (see figure) consists of a front objective mounted at a translation stage with a motorized actuator, and a line-slit imaging spectrograph mounted within a rotary assembly with a rear adaptor to a charged-coupled-device (CCD) camera. Push-broom scanning is carried out by the motorized actuator which can be controlled either manually by an operator or automatically by a computer to drive the line-slit across an image at a focal plane of the front objective. To reduce the cost, the system has been designed to integrate as many as possible off-the-shelf components including the CCD camera and spectrograph. The system has achieved high spectral and spatial resolutions by using a high-quality CCD camera, spectrograph, and front objective lens. Fixtures for attachment of the system to a microscope (U.S. Patent 6,495,818 B1) make it possible to acquire multispectral images of single cells and other microscopic objects.

Mao, Chengye↗

An Architectural Survey of the U12G Tunnel Historic District, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy (DOE), in conjunction with the National Nuclear Security Administration Nevada Field Office (NNSA/NFO), proposes to demolish six buildings and three storage areas located at the U12g Tunnel portal area in Area 12 of the Nevada National Security Site (NNSS). The buildings are 12-358 (Signal Vault); 12-201800 (Storage Quonset Hut); 12-202555 (Walker Shack); 12-868 (Pipe Assembly); 12-B100933 (Electrical Shop); 12-B100944 (Conference Room); and Storage Area 1; Storage Area 2; and Storage Area 3. The buildings and storage areas were selected for demolition as part of the DOE’s Real Property Efficiency Plan to reduce the footprint of unused and non-operational facilities on the NNSS. They are all vacant and have no proposed uses for current or upcoming NNSS missions. Demolition activities constitute an undertaking subject to review under Section 106 of the National Historic Preservation Act (NHPA) (54 United States Code [USC] § 306101) and its implementing regulations, 36 Code of Federal Regulations (CFR) Part 800. Identification efforts began with resources proposed for demolition in federal Fiscal Year (FY) 23. Four buildings were proposed to be demolished in FY23 (12-358, 12-868, 12-201800, and 12-202555). These buildings and the U12g Tunnel Historic District (SHPO No. D444) were recorded in Identification, Evaluation, and Finding of Adverse Effect for the Proposed Demolition of Five Buildings in Area 12, Nevada National Security Site, Nye County, Nevada (Menocal et al. 2023). Identification efforts indicated three buildings (12-358, 12-201800, and 12-868) supported nuclear testing in the U12g Tunnel. The fourth building post-dated the use of U12g Tunnel for nuclear testing activities. The report recommended that three of the four buildings (12-358, 12-201800, 12-868) and the U12g Tunnel Historic District may be eligible for the National Register of Historic Places (NRHP). The report also found that the undertaking would have an adverse effect on the three buildings and on the historic district. The Nevada State Historic Preservation Office (SHPO) concurred with the report’s findings (Reed 2023). The U12g Tunnel was determined eligible as a historic district under the Secretary of the Interior’s (SOI) Significance Criterion A, at the local level, in the context of the Cold War as an underground testing environment for the development of nuclear weapons and to assess the effects of a nuclear explosion on materials and equipment with a period of significance from 1959 to 1971. It was also determined eligible under Significance Criterion C for embodying the distinctive characters of a horizontal tunnel complex used for nuclear testing and as a significant and distinguishable entity. The three buildings were determined to be contributing elements of the district. The undertaking was expanded with the addition of two buildings and three storage areas proposed to be demolished and located within U12g Tunnel Historic District in FY24. These five resources (12-B100933, 12-B100944, and Storage Areas 1, 2, and 3) were recorded in Supplemental Identification, Evaluation, and Finding of Effect for Additional Proposed Demolition at U12g Tunnel, Area 12, Nevada national Security Site, Nye County, Nevada (Brannan et al. 2024). Identification efforts indicated that the two buildings and Storage Area 1 supported nuclear testing in the U12g Tunnel. Storage Area 1 and Storage Area 2 post-dated the nuclear testing activities at U12g Tunnel and were not recommended as contributing elements to the district. The report also found that the undertaking would have an adverse effect on the newly identified buildings and one storage area and on the historic district. The SHPO concurred that the expanded undertaking would result in adverse effects to historic properties (Reed 2025). To resolve these adverse effects, NNSA/NFO, in consultation with the SHPO, is following standard mitigation as stipulated in the 2024 Programmatic Agreement DE-GM58-22NA25554 Among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (hereafter referred to as the NNSS PA). The standard mitigation measures are outlined in Appendix D of the NNSS PA. As such, this architectural survey has been prepared in accordance with Appendix D of the NNSS PA and follows the report format outlined in Appendix F. It includes a historic context that describes the district’s origin, history, and support functions, its significance in the context of nuclear testing on the NNSS, and identifies contributing and non-contributing elements within the district. The report is accompanied by Architectural Resource Assessment (ARA) forms for individual resources and a Historic District Resource Assessment (HDRA) for the U12g Tunnel Historic District. In total, this architectural report identified 32 primary resources within the district boundary. Six of the primary resources were previously identified as contributing elements. An additional 17 resources are recommended as contributing elements to the district for a total of 23 contributing elements. The other nine resources identified are recommended as non-contributing elements to the district.

12-201800↗

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Mellstrom, J. A.↗

Space Station Freedom: Dynamic instrumentation for a large space structure

A proposed approach called Modal Identification Experiment (MIE) for obtaining on-orbit dynamic response measurements on Space Station Freedom, the first of a family of large, flexible space structures is discussed. The Phase 2 conceptual design study which provides a conceptual design of a proposed measurement system and an experimental protocol for inobstrusively collecting dynamic response data critical to characterizing important vibration modes of Space Station Freedom were recently concluded. The case for conducting such a measurement program is presented and the specific MIE objectives that were identified, are listed. The sequence of discrete Space Station Freedom assembly configurations is described, and the Phase 2 conceptual design of the experiment and instrumentation system are defined. In addition, a plan to utilize a space station hydrid scale model in laboratory simulations as part of the design process are discussed.

Raney, John P.↗

Microbiological Characterization of the International Space Station Water Processor Assembly External Filter Assembly S/N 01

The External Filter Assembly (EFA) S/N 01 is a mesh screen filter with a pore size of approximately 300 micron that was installed in the International Space Station (ISS) Water Processor Assembly (WPA) between the Waste Tank and the Mostly Liquid Separator (MLS) on February 11, 2010 to protect clearances in the MLS solenoid valve SV_1121_3. A removal & replacement of the EFA Filter was performed on March 22, 2011 in response to increasing pressure across the Waste Tank solenoid valve SV_1121_1 and the EFA Filter. The EFA Filter was returned on ULF6 and received in the Boeing Huntsville Laboratory on June 13, 2011. The filter was aseptically removed from the housing, and the residual water was collected for enumeration and identification of bacteria and fungi. Swab samples of the filter surface were also collected for microbiological enumeration and identification. Sample analyses were performed by Boeing Huntsville Laboratory and NASA Johnson Space Center Microbiology for comparison. Photographic documentation of the EFA filter was performed using a stereo microscope and environmental scanning electron microscope. This paper characterizes the amount and types of microorganisms on the filter surface and in the residual water from the filter housing following 1 year of utilization in the ISS WPA.

Weir, Natalee↗

Synthetic data-driven deep learning for label-free autonomous atomic force microscopy

Atomic force microscopy (AFM) is a widely used tool for nanoscale characterization across materials science, energy research, and biology. However, its adoption in high-throughput materials discovery and statistically driven studies remains limited by a strong dependence on expert operator input and by the scarcity of annotated experimental AFM datasets needed to enable data-driven automation. Here, we introduce SimuScan, a synthetic-data–driven framework that enables reliable AFM feature identification, segmentation, and targeted imaging without requiring large manually labeled experimental datasets. SimuScan generates tunable, high-fidelity synthetic AFM images of defined morphologies while incorporating realistic experimental artifacts, including tip–sample convolution, noise, flattening distortions, and surface debris. These datasets are shown to support scalable, label-free training of modern deep learning models for AFM analysis. When integrated into data-driven AFM workflows, SimuScan-trained models can locate and analyze nanoscale structures across large datasets and guide targeted follow-up imaging. We validate this approach on nanostructured surfaces, DNA assemblies, and bacterial cells, demonstrating robust generalization across diverse sample types with minimal operator intervention. More broadly, this work establishes a general strategy for generating explicitly conditioned, task-relevant synthetic data to improve the reliability of downstream models in autonomous microscopy.

Millan-Solsona, Ruben [Oak Ridge National Laborato↗

Expansion of the tmRNA sequence database and new tools for search and visualization

Abstract Transfer–messenger RNA (tmRNA) contributes essential tRNA-like and mRNA-like functions during the process of trans-translation, a mechanism of quality control for the translating bacterial ribosome. Proper tmRNA identification benefits the study of trans-translation and also the study of genomic islands, which frequently use the tmRNA gene as an integration site. Automated tmRNA gene identification tools are available, but manual inspection is still important for eliminating false positives. We have increased our database of precisely mapped tmRNA sequences over 50-fold to 97 179 unique sequences. Group I introns had previously been found integrated within a single subsite within the TψC-loop; they have now been identified at four distinct subsites, suggesting multiple founding events of invasion of tmRNA genes by group I introns, all in the same vicinity. tmRNA genes were found in metagenomic archaeal genomes, perhaps a result of misbinning of bacterial sequences during genome assembly. With the expanded database, we have produced new covariance models for improved tmRNA sequence search and new secondary structure visualization tools.

59 BASIC BIOLOGICAL SCIENCES↗

Development of welded metal bellows having minimum effective diameter change

A program of analysis, design, and fabrication was conducted to develop welded metal bellows having a minimum change in effective diameter for cryogenic turbomachinery face seal applications. Linear analysis of the principle types of bellows provided identification of concepts capable of meeting basic operation requirements. For the 6-inch (.152 m) mean diameter, 1.5-inch free length bellows studied, nonlinear analysis showed that opposed and nested toroidal bellows plates stiffened by means of alternating stiffener rings were capable of maintaining constant effective diameter within 0.3% and 0.1% respectively under the operating conditions of interest. Changes in effective diameter were due principally to bellows axial deflection with pressure differential having a lesser influence. Fabrication problems associated with joining the thin bellows plates to the relatively heavy stiffener rings were encountered and precluded assembly and testing of a bellows core. Fabrication problems are summarized and recommended fabrication methods for future effort are presented.

Henschel, J. K.↗

Exploitation of a Validation Hierarchy for Modeling and Simulation

Across engineering there is an evolving need to increase reliance on physics-based simulation to develop, design and optimize engineering systems. This increased reliance on modeling and simulation has highlighted a growing need to transform the confidence that modeling and simulation analysts have in their results into credibility for systems engineers to design and field systems more quickly and with less physical testing. For isolated components of a complex system, where a single discipline may drive product design, this is less of a concern as the relationship is often straightforward and easy to explain. However, when these isolated components are integrated, and are expected to operate in a multi-disciplinary context in which safety critical systems are involved, new concepts and model assurance standards are required. In this paper we address this challenge by showing how a model validation hierarchy can be exploited to identify those model validation experiments that will contribute most to increasing confidence and credibility of modeling and simulation predictions. The approach that is adopted contains four main steps. The first step is the construction of a model validation hierarchy that links subsystems, assemblies, and components to a hierarchy of physical experiments that can be used support model validation. This hierarchy connects the concerns of systems engineers to those of the modeling and simulation analyst in a clear and logical way. The structure and content of this hierarchy is then used in a second step to establish which physical phenomena have the greatest impact on overall system performance metrics. A gap analysis technique, based upon modeling and simulation concerns, is then used to prioritize the important physical phenomenon. Unfortunately, a common outcome of such gap analyses is the identification of many important gaps and so, in the final step of our process, we advocate the use of a global sensitivity analysis as a means to complete the prioritization.

Verification and Validation↗