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NASA NTRS2015

Identifying the "Right Stuff": An Exploration-Focused Astronaut Job Analysis

Industrial and organizational (I/O) psychologists play a key role in NASA astronaut candidate selection through the identification of the competencies necessary to successfully engage in the astronaut job. A set of psychosocial competencies, developed by I/O psychologists during a prior job analysis conducted in 1996 and updated in 2003, were identified as necessary for individuals working and living in the space shuttle and on the International Space Station (ISS). This set of competencies applied to the space shuttle and applies to current ISS missions, but may not apply to longer-duration or long-distance exploration missions. With the 2015 launch of the first 12- month ISS mission and the shift in the 2020s to missions beyond low earth orbit, the type of missions that astronauts will conduct and the environment in which they do their work will change dramatically, leading to new challenges for these crews. To support future astronaut selection, training, and research, I/O psychologists in NASA's Behavioral Health and Performance (BHP) Operations and Research groups engaged in a joint effort to conduct an updated analysis of the astronaut job for current and future operations. This project will result in the identification of behavioral competencies critical to performing the astronaut job, along with relative weights for each of the identified competencies, through the application of job analysis techniques. While this job analysis is being conducted according to job analysis best practices, the project poses a number of novel challenges. These challenges include the need to identify competencies for multiple mission types simultaneously, to evaluate jobs that have no incumbents as they have never before been conducted, and working with a very limited population of subject matter experts. Given these challenges, under the guidance of job analysis experts, we used the following methods to conduct the job analysis and identify the key competencies for current and potential future missions.

Barrett, J. D.↗

NASA NTRS2015

Identification and Analysis of National Airspace System Resource Constraints

This analysis is the deliverable for the Airspace Systems Program, Systems Analysis Integration and Evaluation Project Milestone for the Systems and Portfolio Analysis (SPA) focus area SPA.4.06 Identification and Analysis of National Airspace System (NAS) Resource Constraints and Mitigation Strategies. "Identify choke points in the current and future NAS. Choke points refer to any areas in the en route, terminal, oceanic, airport, and surface operations that constrain actual demand in current and projected future operations. Use the Common Scenarios based on Transportation Systems Analysis Model (TSAM) projections of future demand developed under SPA.4.04 Tools, Methods and Scenarios Development. Analyze causes, including operational and physical constraints." The NASA analysis is complementary to a NASA Research Announcement (NRA) "Development of Tools and Analysis to Evaluate Choke Points in the National Airspace System" Contract # NNA3AB95C awarded to Logistics Management Institute, Sept 2013.

Smith, Jeremy C.↗

NASA NTRS2012

An Ontology for State Analysis: Formalizing the Mapping to SysML

State Analysis is a methodology developed over the last decade for architecting, designing and documenting complex control systems. Although it was originally conceived for designing robotic spacecraft, recent applications include the design of control systems for large ground-based telescopes. The European Southern Observatory (ESO) began a project to design the European Extremely Large Telescope (E-ELT), which will require coordinated control of over a thousand articulated mirror segments. The designers are using State Analysis as a methodology and the Systems Modeling Language (SysML) as a modeling and documentation language in this task. To effectively apply the State Analysis methodology in this context it became necessary to provide ontological definitions of the concepts and relations in State Analysis and greater flexibility through a mapping of State Analysis into a practical extension of SysML. The ontology provides the formal basis for verifying compliance with State Analysis semantics including architectural constraints. The SysML extension provides the practical basis for applying the State Analysis methodology with SysML tools. This paper will discuss the method used to develop these formalisms (the ontology), the formalisms themselves, the mapping to SysML and approach to using these formalisms to specify a control system and enforce architectural constraints in a SysML model.

Wagner, David A.↗

NASA NTRS2017

Sensitivity Analysis of Multidisciplinary Rotorcraft Simulations

A multidisciplinary sensitivity analysis of rotorcraft simulations involving tightly coupled high-fidelity computational fluid dynamics and comprehensive analysis solvers is presented and evaluated. An unstructured sensitivity-enabled Navier-Stokes solver, FUN3D, and a nonlinear flexible multibody dynamics solver, DYMORE, are coupled to predict the aerodynamic loads and structural responses of helicopter rotor blades. A discretely-consistent adjoint-based sensitivity analysis available in FUN3D provides sensitivities arising from unsteady turbulent flows and unstructured dynamic overset meshes, while a complex-variable approach is used to compute DYMORE structural sensitivities with respect to aerodynamic loads. The multidisciplinary sensitivity analysis is conducted through integrating the sensitivity components from each discipline of the coupled system. Numerical results verify accuracy of the FUN3D/DYMORE system by conducting simulations for a benchmark rotorcraft test model and comparing solutions with established analyses and experimental data. Complex-variable implementation of sensitivity analysis of DYMORE and the coupled FUN3D/DYMORE system is verified by comparing with real-valued analysis and sensitivities. Correctness of adjoint formulations for FUN3D/DYMORE interfaces is verified by comparing adjoint-based and complex-variable sensitivities. Finally, sensitivities of the lift and drag functions obtained by complex-variable FUN3D/DYMORE simulations are compared with sensitivities computed by the multidisciplinary sensitivity analysis, which couples adjoint-based flow and grid sensitivities of FUN3D and FUN3D/DYMORE interfaces with complex-variable sensitivities of DYMORE structural responses.

Wang, Li↗

NASA NTRS2018

Aeromechanics Analysis of a Distortion-Tolerant Fan with Boundary Layer Ingestion

A propulsion system with Boundary Layer Ingestion (BLI) has the potential to significantly reduce aircraft engine fuel burn. But a critical challenge is to design a fan that can operate continuously with a persistent BLI distortion without aeromechanical failure -- flutter or high cycle fatigue due to forced response. High-fidelity computational aeromechanics analysis can be very valuable to support the design of a fan that has satisfactory aeromechanic characteristics and good aerodynamic performance and operability. Detailed aeromechanics analyses together with careful monitoring of the test article is necessary to avoid unexpected problems or failures during testing. In the present work, an aeromechanics analysis based on a three-dimensional, time-accurate, Reynolds-averaged Navier-Stokes computational fluid dynamics code is used to study the performance and aeromechanical characteristics of the fan in both circumferentially-uniform and circumferentially-varying distorted flows. Pre-test aeromechanics analyses are used to prepare for the wind tunnel test and comparisons are made with measured blade vibration data after the test. The analysis shows that the fan has low levels of aerodynamic damping at various operating conditions examined. In the test, the fan remained free of flutter except at one near-stall operating condition. Analysis could not be performed at this low mass flow rate operating condition since it fell beyond the limit of numerical stability of the analysis code. The measured resonant forced response at a specific low-response crossing indicated that the analysis under-predicted this response and work is in progress to understand possible sources of differences and to analyze other larger resonant responses. Follow-on work is also planned with a coupled inlet-fan aeromechanics analysis that will more accurately represent the interactions between the fan and BLI distortion.

Propulsion Aeroelasticity↗

NASA NTRS2018

PYSAT: Python Satellite Data Analysis Toolkit

A common problem in space science data analysis is combining complementary data sources that are provided and analyzed in different formats and programming languages. The Python Satellite Data Analysis Toolkit (pysat) addresses this issue by providing an open source toolkit that implements the general process of space science data analysis, from beginning to end, in an instrumentindependent manner. This toolkit uses an Instrument object that enables systematic analysis of science data from a variety of platforms within a single interface. Basic functions such as downloading, loading, and cleaning are included for all supported instruments. Common analysis routines are also included, which are instrument and data source independent. A nanokernel is used to provide instrument independence, it is attached to the Instrument object and mediates the systematic and arbitrary modification of loaded data. Pysat uses the nanokernel to improve the rigor of time series analysis, support onthefly orbit determination, and cleanly span file breaks. Pysat's functions and higherlevel scientific analysis features are validated through the use of unit testing. Further adoption by the community provides a set of scientific results produced by a common core, constituting a distributed heritage that supports the validity of the underlying processing and scientific output. These features are used to demonstrate consistency between derived electron density profiles and measured ion drifts, particularly downward ion drifts in the afternoon hours during extreme solar minimum. Pysat builds upon open source Python software that is freely available and encourages communitydriven development.

Stoneback, R.A.↗

NASA NTRS2019

NDARC NASA Design and Analysis of Rotorcraft - Input, Appendix 10

The NASA Design and Analysis of Rotorcraft (NDARC) software is an aircraft system analysis tool that supports both conceptual design efforts and technology impact assessments. The principal tasks are to design (or size) a rotorcraft to meet specified requirements, including vertical takeoff and landing (VTOL) operation, and then analyze the performance of the aircraft for a set of conditions. For broad and lasting utility, it is important that the code have the capability to model general rotorcraft configurations, and estimate the performance and weights of advanced rotor concepts. The architecture of the NDARC code accommodates configuration flexibility, a hierarchy of models, and ultimately multidisciplinary design, analysis, and optimization. Initially the software is implemented with low-fidelity models, typically appropriate for the conceptual design environment. An NDARC job consists of one or more cases, each case optionally performing design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance calculation, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. For analysis tasks, the aircraft description can come from the sizing task, from a previous case or a previous NDARC job, or be independently generated (typically the description of an existing aircraft). The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. For each component, attributes such as performance, drag, and weight can be calculated; and the aircraft attributes are obtained from the sum of the component attributes. Description and analysis of conventional rotorcraft configurations is facilitated, while retaining the capability to model novel and advanced concepts. Specific rotorcraft configurations considered are single-main-rotor and tail-rotor helicopter, tandem helicopter, coaxial helicopter, and tiltrotor. The architecture of the code accommodates addition of new or higher-fidelity attribute models for a component, as well as addition of new components.

NDARC↗

NASA NTRS2019

Thermal & Fluids Analysis and the NASA Launch Services Program

This presentation provides the What, Where, Why, and How of the thermal and fluids analysis disciplines within the Launch Services Program (LSP). The LSP manages all commercial launch services to match NASA science mission payloads to the appropriate launch system. The Flight Analysis Division within the LSP provides multi disciplinary analysis support of these flight systems to characterize payload and launch vehicle environments from payload mate to upper stage through on orbit separation. The Thermal Analysis and Fluids Analysis teams are two distinct groups within the Flight Analysis Division of the LSP who cover a wide array of standard and non standard analytical tasks. These teams offer a significant benefit to both the payload design and integration team and the launch vehicle supplier. These benefits, along with the tools and methods are described in this talk to inform engineers and analysts from both sides of the launch system interface how the LSP Thermal and Fluids Analysis teams can benefit the success of their mission.

Fortenberry, Cindy↗

NASA NTRS2020

TURBOMAT-FR: Turbomachinery Aeroelastic Forced Response Analysis Automation Using MATLAB® Part 2

The primary aim of this effort is to develop a software tool named “Turbomachinery Aeroelastic Analysis Tool for Forced Response (TURBOMAT-FR)” using MATLAB® (The MathWorks, Inc.) scripts. The tool will aid in performing routine forced response analysis of turbomachinery fan blades with the aid of the modal summation method (MSUM). The MSUM approach requires a modal solution consisting of modal displacements, frequencies, and stresses. The MATLAB® scripts facilitate easy extraction of the required quantities from the computational fluid dynamics (CFD) and MSC Nastran (Hexagon AB) solution files. These quantities are subsequently utilized by the MSUM approach to perform a complete forced response analysis using the MATLAB® scripts. The MATLAB® scripts in TURBOMAT-FR are utilized in postprocessing of the MSC Nastran finite element analysis outputs in three types of solutions or steps, namely (1) stresses and displacements from static or steady response solution, (2) unsteady stresses and displacements from direct forced response solution, and (3) modal solution containing modal displacements and modal stresses. In step (4), separate MATLAB® scripts are also developed to read the processed outputs in step (3) and perform forced response analysis using MSUM. It should be noted that the direct forced response solution from step (2) will provide for a comparison with those obtained from the MSUM approach in steps (3) and (4). The TURBOMAT-FR MATLAB® scripts mentioned previously are presented in two reports designated Parts 1 and 2. Part 1 presents the scripts needed to accomplish steps (1) and (2). The current report, Part 2, presents the scripts needed to accomplish steps (3) and (4), noted previously. The TURBOMAT-FR MATLAB® scripts provided here in Part 2 facilitate the calculation of unsteady stresses using MSUM and provide an automated procedure associated with aeroelastic forced response analysis with different pressure files. The unsteady stresses calculated using MSUM can be compared with those presented in Part 1. A cantilevered blade-alone model subjected to a realistic pressure loading to a boundary was used for static and unsteady direct forced response analysis to demonstrate the effectiveness of the TURBOMATFR MATLAB® scripts.

T S R Reddy↗

NASA NTRSDate not supplied

Soluble Organic Matter (SOM) analysis of the Hayabusa2 samples: The first results

The Hayabusa2 spacecraft successfully collected the surface and possible sub-surface materials of the asteroid 162173 Ryugu. Ryugu is a C-type asteroid characterized by a low-albedo surface probably consisting of hydrous minerals and carbonaceous materials. [1] The direct optical and spectral analysis of the returned samples indicates that Ryugu material is dominated by hydrous carbonaceous chondrite-like matter (similar to CI chondrites) [2]. Since carbonaceous chondrites have generally yielded various types of organic matter, the collected Ryugu grains are expected to contain diverse types of organic compounds including bio-related molecules. The occurrence of organic compounds in the Ryugu surface will provide clues to the evolution of prebiotic molecules and their preservations associated with aqueous alteration of the primitive asteroid. The initial analysis of soluble organic matter (SOM) of the Hayabusa2-returned samples has been performed by an international team consisting of 32 members. Because the sample amount available for comprehensive SOM analyses is limited, and because the SOM is expected to be present as a complex mixture of various types of organic compounds with very small concentrations of each compound, high-sensitivity and high-resolution analytical techniques have been developed using carbonaceous meteorites [e.g. 3]. Two aggregate samples of the Ryugu grains (A106 and C107) were allocated for the solvent extractions and bulk carbon (C), hydrogen (H), nitrogen (N), sulfur (S) and oxygen (O) measurements. The A106 sample was collected during the 1st sampling in February 2019 and the C107 sample was collected during the 2nd sampling in July 2019 after the Small Carry Impactor (SCI) operation. They consist mainly of particles smaller than 1 mm in diameter, and each sample mass was 38-39 mg. They were firstly investigated spectroscopically in the near infrared wavelength range by the Stone Team prior to the solvent extractions. Other small grains (A0080 and C0057) were also allocated for this study to investigate the spatial distribution of organic compounds on the sample surface. The extraction and analytical measurements implemented by the SOM Team are summarized in Figure 1. Each powder sample was extracted sequentially with non-polar to polar solvents, i.e., hexane, dichloromethane (DCM), methanol (MeOH) and H2O, for non-targeted analysis to reveal the compound composition. Each solvent extract was analyzed by solution state nuclear magnetic resonance (NMR) spectroscopy [4], Fourier transform- ion cyclotron resonance/mass spectrometry (FT-ICR/MS) with ESI and APPI ionization [5] and by high-resolution mass spectroscopy using Orbitrap MS coupled with nano-liquid chromatography (nanoLC/Orbitrap MS) [6], and using two dimensional gas chromatography/mass spectrometry (GC×GC/MS). The extracted residues were passed to the Chemistry Team for further inorganic element analysis. The other powder sample was subjected to the hot water extraction for amino acid analyses including chiral isomer separation, which was performed by three-dimensional (3D) high-performance liquid chromatography (HPLC) with high-sensitivity fluorescence detection (FD) [7] and by HPLC/FD coupled with quadrupole-time of flight/mass spectrometry (QToF/MS) [8]. After the hot water extraction, the residue was split into two halves. One half was further extracted with hydrochloric acid (HCl) to analyze for amino acids in bound-form. The other half was sequentially extracted with DCM/MeOH (1/1) to analyze semi-polar compounds such as polycyclic aromatic hydrocarbons (PAHs) by GC/MS, followed by further extraction with formic acid to analyze polar heterocyclic compounds, and subsequent extraction with HCl to detect bound-form polar compounds. The extracted residues were passed to the IOM Team for the analysis of insoluble organic matter (IOM). Compound-specific stable isotope analyses will be performed using GC/combustion/isotope ratio mass spectrometry (GC/C/IRMS) if the compound concentration is high enough to enable such an isotopic measurement. All extraction procedures were performed on an ISO 6 (Class 100) clean bench inside an ISO 5 (Class 1000) clean room. Baked serpentine powder was also analyzed as a procedural blank. In situ organic compound analysis with the molecular imaging was performed using desorption electrospray ionization (DESI) equipped with Orbitrap MS [9, 10], followed by spatial imaging of organic compounds using ToF/secondary ion mass spectrometry (ToF/SIMS) [11]. The bulk chemical and isotopic compositions of CNS and HO were determined using nano-elemental analysis/isotope ratio mass spectrometry (nanoEA/IRMS) [12] and EA/pyrolysis/IRMS, respectively. We have identified a variety of indigenous organic compounds in the extracts of both A106 and C107 samples. The Ryugu grains host organic molecules under the high-vacuum and cosmic-ray irradiation environment of the asteroid surface. The analysis of extracted molecules is in progress, and the first results will be presented at the symposium.

Hiroshi Naraoka↗

NASA NTRS2024

SUPIN: A Tool for the Aerodynamic Design and Analysis of Supersonic Inlets

The Supersonic Inlet Design and Analysis Tool (SUPIN) is a computational program that performs geometric modeling and aerodynamic design and analysis of a set of supersonic inlets whose types include the axisymmetric pitot, three-dimensional pitot, axisymmetric, two-dimensional, two-dimensional bifurcated-duct, and streamline-traced inlets. The inlets are modeled by dividing the inlet flowpath into components that start at the freestream and ends at the engine face. The primary components of the inlet include the external supersonic diffuser, throat section, and subsonic diffuser. Each component is characterized by a set of inputs that include geometric and aerodynamic factors. Examples of the geometric factors are angles, lengths, area ratios, and coordinates that describe the geometry of the components. Examples of the aerodynamic factors are Mach numbers, flow ratios, and pressure ratios that set constraints or desired aerodynamic properties of the component. These input factors are specified within a text-based input data file that is read into SUPIN. SUPIN is a Fortran 95 program that performs the inlet design and analysis as a batch or non-interactive process. SUPIN writes output data files describing the inlet geometry and aerodynamic performance. SUPIN uses analytic, empirical, and numerical methods to perform the inlet design and analysis. The inlet geometry is constructed using planar and three-dimensional geometry constructs and is represented by coordinates, angles, areas, profiles, and surfaces. Surfaces are output in the form of a Plot3D surface grid file. SUPIN does have some capability to automatically generate planar and three-dimensional, multi-block, structured grids for computational fluid dynamics (CFD) analysis. The aerodynamic analysis performed by SUPIN computes quasi-one-dimensional properties, such as Mach numbers, pressures, and temperatures, through the inlet flowpath. Planar aerodynamic properties, such as those for shock and Mach waves, are computed for the supersonic compression of the external supersonic diffuser and throat section. The inlet performance is characterized by the inlet flow rates, total pressure recovery, and inlet drag. The primary intent of this document is to describe the usage of SUPIN. The methods used within SUPIN are documented and may serve as a useful reference for understanding the aerodynamic design and analysis of supersonic inlets.

supersonic inlets↗

DOE OSTI2026

Validation of the DESI DR2 Ly$α$ forest full-shape analysis

We present the validation of the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) Lyman-$α$ (Ly$α$) forest full-shape analysis. This analysis combines three-dimensional Ly$α$ forest auto-correlations and cross-correlations with quasars to extract information from both the baryon acoustic oscillation (BAO) feature and the broadband clustering signal, with primary emphasis on the Alcock-Paczynski (AP) measurement. Compared to the DESI DR1 analysis, the DR2 validation uses substantially larger and more realistic mock datasets, including CoLoRe 2LPT and AbacusSummit Ly$α$ forest simulations. The modeling framework is also improved through analytic marginalization over small scales ($<10$$h^{-1}$Mpc) and the impact of ultraviolet background fluctuations. The validation program was completed prior to unblinding and defines quantitative requirements for the cosmological parameters of interest, which are evaluated using hundreds of mock realizations. We further test the analysis through independent fits to the auto- and cross-correlations, multiple catalog splits, and a broad suite of analysis and modeling variations applied to both mocks and blinded observational data. We find that the BAO and AP parameters satisfy all validation requirements and remain stable across all tests. In contrast, mock studies reveal a significant bias in the inferred growth-rate parameter $fσ_8$, leading us to exclude this measurement from the final analysis. The consistency across mocks, data splits, and robustness tests demonstrates that the DR2 Ly$α$ full-shape analysis provides a reliable and substantially improved broadband AP measurement over previous Ly$α$ forest studies.

Herbold, M. [Chicago U., KICP; Ohio State U.] (ORC↗

DOE OSTI2026

Performance evaluation of neutron noise analysis in detecting special nuclear materials

Reliable and rapid inspection techniques play a vital role in preventing illicit trafficking of special nuclear materials. Active interrogation systems using neutrons produced by portable, high-flux deuterium-deuterium or deuterium-tritium neutron generators are being actively developed as a secondary scanning tool for this purpose. In this study, a neutron noise analysis-based approach for detecting unshielded and shielded special nuclear materials by using a pulsed deuterium-tritium neutron generator was evaluated. Here, this approach analyzes the fluctuation of neutron counts. Its performance was quantified with regard to time-to-detection to achieve a minimum probability of detection of 99% and a probability of false alarm of less than 1% considering various amounts of special nuclear materials and different shielding configurations. It was demonstrated that this approach could detect 17 uranium slugs in 5 s given a neutron generator yield of 8.1 × 10 7 n/s. These slugs could be detected within a reasonable time frame (200 s) when they were shielded by 10.16 cm of high-density polyethylene. The results obtained using the neutron noise analysis approach were compared with those obtained using the commonly used differential die-away analysis technique, a sensitive technique for detecting the presence of fissile materials by utilizing the prompt fission neutrons produced when the source neutrons from a neutron generator are completely diminished. For example, the time to detect 2 unshielded uranium slugs was 2.1 s when using the differential die-away analysis technique; it increased to 93 s for the neutron noise analysis approach. Although the noise analysis-based approach exhibits an overall performance which is not as good as that of differential die-away, neutron noise provides an alternative method for effective detection of special nuclear materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRSDate not supplied

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

This paper presents a technical approach to improve the confidence in the systems analysis process by integrating Uncertainty Quantification (UQ) techniques within a Model-Based Systems Analysis and Engineering (MBSA&E) framework. The MBSA&E architecture uses system models and multidisciplinary analytical solutions as central artifacts for system design and analysis. The integration of UQ enables engineers to assess and mitigate uncertainties associated with a system model, design parameters, and constraint inputs, leading to more complete design studies and further informed decision-making processes. The proposed approach leverages the strengths of MBSA&E and extends it with a UQ methodology to quantify uncertainties in the input parameters and to trace the uncertainties as they propagate throughout the system model. To demonstrate the effectiveness of an integrated MBSA&E-UQ approach, a case study involving a simplified analysis of a Transonic Truss-Braced Wing (TTBW) concept vehicle is performed. This integration enables a more comprehensive evaluation of system performance and behavior under uncertainty and a more robust approach for system design and analysis. Lastly, the paper addresses the challenges and considerations associated with integrating UQ into an MBSA&E framework.

systems analysis↗

NASA NTRSDate not supplied

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

systems analysis↗

DOE OSTI2025

TRANSP integrated modeling code for interpretive and predictive analysis of tokamak plasmas

This paper provides a comprehensive review of the TRANSP code, a sophisticated tool for interpretive and predictive analysis of tokamak plasmas, detailing its major capabilities and features. It describes the equations for particle, power, and momentum balance analysis, as well as the poloidal field diffusion equations. The paper outlines the spatial and time grids used in TRANSP and details the equilibrium assumptions and solvers. Various models for heating and current drive and radiation, including updates to the NUBEAM model, are discussed. The handling of large-scale events such as sawtooth crashes and pellet injections is examined, along with the predictive capabilities for advancing plasma profiles. The integration of TRANSP with the ITER Integrated Modeling and Analysis Suite (IMAS) is highlighted, demonstrating enhanced data access and analysis capabilities. Additionally, the paper discusses best practices and continuous integration techniques to enhance TRANSP's robustness. The suite of TRANSP tools, designed for efficient data analysis and simulation, further supports the optimization of tokamak operations and coupling with other tokamak codes. Continuous development and support ensure that TRANSP remains a major code for the analysis of experimental data for controlled thermonuclear fusion, maintaining its critical role in supporting the optimization of tokamak operations and advancing fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

CSP Systems Analysis 2022-2024 (Final Technical Report)

The CSP Systems Analysis project estimates the current market cost of CSP subsystems and technologies for use by the DOE Program and within NREL analysis tools. The project addresses upgrades to NREL's System Advisor Model (SAM) related to CSP, as well as development of new modules within SAM to expand the types of CSP systems that can be simulated and new tools for evaluating CSP subsystem performance or optimizing CSP system layouts, for example, SolarPILOT and SolTrace. The project evaluates the potential cost and performance of new CSP-relevant technologies and generally includes assessment of CSP technologies in support of the DOE subprogram. A primary goal of the CSP System Analysis project is to provide timely and accurate cost data to the DOE to assess the current state of CSP technologies as well as predict performance and cost for pre-commercial and emerging technologies that may impact the industry. Prior work in this task has produced technology cost reports and roadmaps for DOE and highlighted promising research paths that could reduce overall CSP cost, such as the supercritical CO2 power cycle and molten-salt trough systems. CSP Systems Analysis produces modeling tools to evaluate the performance of CSP systems, subsystems, or components, and journal articles, conference papers, technical reports and databases to disseminate information to the CSP industry. CSP technology costs are estimated and tracked using these tools as well as analysis of literature and industry sources. The CSP modeling tools and NREL analysis results are used by researchers; government, financial, and industry analysts; and other CSP stakeholders. The purpose of this final technical report is to summarize the key accomplishments of the past three years of this project. The project was divided into seven separate tasks, and in what follows, we describe the background, objectives, key accomplishments, and path forward for each task within the project, with one section of this report summarizing each task.

14 SOLAR ENERGY↗

NASA NTRS2006

An Efficient Approach for the Reliability Analysis of Phased-Mission Systems with Dependent Failures

We consider the reliability analysis of phased-mission systems with common-cause failures in this paper. Phased-mission systems (PMS) are systems supporting missions characterized by multiple, consecutive, and nonoverlapping phases of operation. System components may be subject to different stresses as well as different reliability requirements throughout the course of the mission. As a result, component behavior and relationships may need to be modeled differently from phase to phase when performing a system-level reliability analysis. This consideration poses unique challenges to existing analysis methods. The challenges increase when common-cause failures (CCF) are incorporated in the model. CCF are multiple dependent component failures within a system that are a direct result of a shared root cause, such as sabotage, flood, earthquake, power outage, or human errors. It has been shown by many reliability studies that CCF tend to increase a system's joint failure probabilities and thus contribute significantly to the overall unreliability of systems subject to CCF.We propose a separable phase-modular approach to the reliability analysis of phased-mission systems with dependent common-cause failures as one way to meet the above challenges in an efficient and elegant manner. Our methodology is twofold: first, we separate the effects of CCF from the PMS analysis using the total probability theorem and the common-cause event space developed based on the elementary common-causes; next, we apply an efficient phase-modular approach to analyze the reliability of the PMS. The phase-modular approach employs both combinatorial binary decision diagram and Markov-chain solution methods as appropriate. We provide an example of a reliability analysis of a PMS with both static and dynamic phases as well as CCF as an illustration of our proposed approach. The example is based on information extracted from a Mars orbiter project. The reliability model for this orbiter considers the various phases of Launch, Cruise, Mars Orbit Insertion, and Orbit. Some of the CCF for the orbiter in this mission include environmental effects, such as micrometeoroids, human operator errors, and software errors.

reliability analysis↗