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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 37 records · Page 2

Application of Analytical Hierarchy Process for Narrowing Down Nep Candidate Reactor Designs

Nuclear electric propulsion (NEP)-powered vehicles have been contemplated for human Mars missions. The nuclear power system contemplates using a high temperature light-weight nuclear reactor for the production of electrical power in the range of 2-5 MWe with a 3-10 year service life. A myriad of technology options exist for achieving these mission objectives. The analytic hierarchy process (AHP), a multi-attribute decision method, is being used to narrow down the candidate designs. The AHP is a structured decision process that fuses model-supplied quantitative data with subjective assessments to facilitate decisions that involve multiple competing criteria. Proven end-to-end nuclear design and systems analysis tools will be used to provide quantitative performance data such as end-to-end system reliability, system robustness to recover from off-normal conditions, system specific weight (α in kg/kWe), and the ability to meet the service life-time and power level requirements. Three high assay low enriched uranium (HALEU) reactor concepts, namely, gas-, heat pipe- and pumped liquid-cooled nuclear cores coupled to a He/Xe gas or supercritical CO2- Brayton power conversion system are being modeled using the AHP to understand the trade-offs associated with these design combinations. In addition to the reactor and power conversion options, there are a myriad of additional components and subsystems – e.g., radiators, heat exchangers, and recuperators – that also figure into the evaluation process. The choice of the right overall system is a multidimensional problem that has to include not only quantitative data, but also the so called “external factors”, examples of which include the component and subsystem Technology Readiness Levels (TRLs), the associated Advancement Degrees of Difficulty (AD2), the cost and schedule required to achieve a technical maturity consistent with mission infusion, alignment with the priorities of NASA’s Space Nuclear Propulsion program, and alignment with other ongoing government and commercial investments in micro reactors. Focused expert elicitations form the basis for qualitative data set. As a final step, decision-makers individually express their opinions regarding the relative importance of the criteria and preferences among the alternatives through pairwise comparisons. The paper will describe the AHP approach, progress to-date applying it to the NEP human Mars mission problem, and preliminary results. Use of AHP provides sufficient flexibility for incorporating industry input at different stages as the technologies evolve through additional research and development. It is expected that the decision process will be ongoing and expanded to examine additional options and technology choices, culminating in a defensible set of candidate reactor concepts that will form the basis for developing a multi-year NEP technology maturation strategy. .

Dasari V Rao↗

Application of Analytical Hierarchy Process for Narrowing Down Nep Candidate Reactor Designs

NASA is currently studying the possibility of human exploration of Mars in the late 2030s timeframe using a hybrid nuclear electric propulsion (NEP)/chemical propulsion system. Present analyses indicate such a mission could require a reactor power system in the range of 2 to 6 MWe operating for approximately 3 years. At present, the Technology Readiness Levels (TRL) of key NEP technologies are still low, implying that significant technology development activities must be undertaken prior to making informed design selections for an integrated propulsion system. NASA’s Space Nuclear Propulsion (SNP) project has recently undertaken an in-depth effort to identify NEP candidate technologies and determine the required developmental work to mature these technologies to the point where they could realistically support the design and assembly of a full NEP system. A version of the Analytical Hierarchy Process is being employed to narrow the technology candidates for SNP investment planning. This multi-attribute decision-making process relies on quantified technical inputs and the judgement of Subject Matter Experts (SMEs) to evaluate technology options against key technical and programmatic Figures-of-Merit (FOM) at the subsystem and optimized system level. The process and an example evaluation of nuclear fuel/moderator combinations in a sodium heat pipe honeycomb-geometry reactor concept are described. The evaluation and analysis methodology described in this paper can be employed for pairwise comparisons between reactor concepts and technology choices as new data become available.

Dasari V Rao↗

Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

Tavana, Madjid↗

Strain gage calibration of a complex wing

Modern complex structural arrangements have complicated the task of measuring flight loads with calibrated strain gages. This paper examines the use of a relatively simple structural model to characterize the load responses of strain gages located on various spars of a delta wing. Strains measured during a laboratory load calibration of a wing structure are compared with calculations obtained from a simplified NASA structural analysis (NASTRAN) model. Calculated and measured influence coefficient plots that show the shear, bending, and torsion characteristics of typical strain-gage bridges are presented. Typical influence coefficient plots are given for several load equations to illustrate the derivation of the equations from the component strain-gage bridges. A relatively simple structural model was found to be effective in predicting the general nature of strain distributions and influence coefficient plots. The analytical processes are shown to be useful in obtaining a good load calibration. The analytical processes cannot, however, be used in lieu of an actual load calibration of an aircraft wing.

Jenkins, J. M.↗

The use of a simplified structural model as an aid in the strain gage calibration of a complex wing

The use of a relatively simple structural model to characterize the load responses of strain gages located on various spars of a delta wing is examined. Strains measured during a laboratory load calibration of a wing structure are compared with calculations obtained from a simplified structural analysis model. Calculated and measured influence coefficient plots that show the shear, bending, and torsion characteristics of typical strain gage bridges are presented. Typical influence coefficient plots are shown for several load equations to illustrate the derivation of the equations from the component strain gage bridges. A relatively simple structural model was found to be effective in predicting the general nature of strain distributions and influence coefficient plots. The analytical processes are shown to be an aid in obtaining a good load calibration. The analytical processes cannot, however, be used in lieu of an actual load calibration of an aircraft wing.

Jenkins, J. M.↗

Analogue implementation of analytic signal processing for pulse-echo systems

An alternative to rectification is proposed for detection of an ultrasonic signal. This method is especially useful in medical and non-destructive evaluation (nde) applications. With this method, the magnitude of the complex analytic signal is used to define the envelope of the ultrasonic waveform. The square of this quantity has been shown elsewhere to be equal to the true rate-of-arrival of energy. An earlier study, using digital data processing, has already demonstrated the superior resolvability of closely spaced interfaces obtained with the analytic signal magnitude, as compared to conventional rectification. Here, an analogue implementation is presented which utilizes single-sideband techniques to obtain both quadrature components of the analytic signal and its magnitude. A conventional transducer, pulser, and receiver are used.

Gammell, P. M.↗

A Processing and Analytics System for Microscopy Data Workflows: The Pycroscopy Ecosystem of Packages

Major advancements in fields as diverse as biology and quantum computing have relied on a multitude of microscopy techniques. Despite the considerable proliferation of these instruments, significant bottlenecks remain in terms of processing, analysis, storage, and retrieval of the acquired datasets. Aside from lack of file standards, individual domain-specific analysis packages are often disjoint from the underlying datasets, and thus keeping track of analysis and processing steps remains tedious for the end-user, hampering reproducibility. Here, in this study, the pycroscopy ecosystem of packages is introduced, an open-source python-based ecosystem underpinned by a common data model. The data model, termed the N-dimensional spectral imaging data format, is realized in pycroscopy's sidpy package. This package is built on top of dask arrays, thus leveraging dask array attributes, but expanding them to accelerate microscopy relevant analysis and visualization. Several examples of the use of the pycroscopy ecosystem to create workflows for data ingestion and analysis of scanning transmission electron microscopy (STEM) and scanning probe microscopy data are shown. Adoption of such standardized routines will be critical to usher in the next generation of autonomous instruments where processing, computation, and meta-data storage will be critical to overall experimental operations.

97 MATHEMATICS AND COMPUTING↗

Measurement of Plutonium Ratios for CRM 137A Recertification

This report documents the analytical methodologies used by the Chemical and Isotopics Mass Spectrometry (CIMS) Group at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) for plutonium isotopic ratio characterizations on purified ~1 mg units prepared by Lawrence Livermore National Laboratory (LLNL) from a mother solution created from an existing 250 mg unit of certified reference material (CRM) 137. The analytical processes described are designed to maintain traceability of the final certified attributes and to eliminate sources of systematic bias for the measurements described. The measurands for certification are the plutonium isotope ratios: 238 Pu/ 239 Pu, 240 Pu/ 239 Pu, 241 Pu/ 239 Pu, and 242 Pu/ 239 Pu. The preparation and analytical process included the following activities: Preparation of reference materials to be used as calibrants to establish traceability to the SI unit of mass for the isotopic analyses and quality controls. For the plutonium isotopic analyses, CRM 128 (a CRM comprising equal atoms of 239 Pu and 242 Pu) was used as the primary calibrant; Each CRM 137A unit was reconstituted using dilute high-purity HNO3. From each, seven replicates were distributed for the isotopic characterizations by thermal ionization mass spectrometry (TIMS) using the total evaporation (TE) method for isotope ratio measurements and MC-ICP-MS using a dynamic peak hooping method for secondary isotope ratio measurements; Due to time delay in the analyses from the last purification of the original CRM 137 mother solution by LLNL, an aliquot of the three provided plutonium units was purified using Eichrom TEVA separation methods to remove americium in-growth and uranium impurities; Minimally corrected data were reported from each analysis using reporting templates provided by the New Brunswick Laboratory Program Office (NBL PO) for the specific methods used for isotopic measurements. In addition, a copy of the instrument exports, Excel templates for isotopic data corrections, and the uncertainty budgets completed with the GUM Workbench software package were submitted to NBL PO.

07 ISOTOPE AND RADIATION SOURCES↗

Fast methods for multisite charge transfer. Processes II. Analytic nuclear gradients and nonadiabatic dynamics for cCASSCF(1,n) and cCASSCF(2n-1,n) wavefunctions

In this work we derive and implement analytic nuclear gradients and derivative couplings for a constrained complete active space self-consistent field with a small active space designed to model electron or hole transfer. Using a Lagrangian formalism, we are able to differentiate both the CASSCF energy and the constraint (which is required for smooth surfaces over a wide range of parameter space), and the resulting efficient algorithm can be immediately applied to nonadiabatic dynamics simulations of charge transfer processes. Here, we run initial surface-hopping simulations of a proton coupled electron transfer event for a phenoxyl–phenol system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TripleGraph

RDF triplestores are great tools for online graph analytic processing (i.e., graph pattern query processing), but they do not provide graph mining capabilities (e.g., PageRank, connected-component analysis, node eccentricity, etc.). The software title “TripleGraph” is a graph analysis toolkit, which uses an RDF triplestore as its backend for creating, manipulating, mining, and programming with large scale property graphs. It allows users to run various graph mining algorithms easily. User can import edgelist-formatted (homogeneous graph) or JSON-formatted graph (property graph) into the RDF triplestore using the provided tool and perform various analysis such as (1) Node/edge retrieval and manipulation, (2) Pathfinding between two given nodes, (3) Running graph mining algorithms (PageRank/Personalized PageRank, Single Source Shortest Path/Multi-Source Shortest Path, Connected Component, Node Eccentricity, Peer Pressure Clustering). It supports standard graph data format and works with a standard SPARQL endpoint like Jena Fuseki. It allows users to perform online graph analytic processing and graph mining on the same platform (a triplestore).

Sangkeun, MattLee↗

Launch Vehicle/Carrier Interaction, Improving the Analytical Integration Process

A goal of the aerospace industry is to reduce the cost of space transportation by a significant within the next decade. The present cost of launching a space transportation system which includes propulsion system, vehicle, carrier, and payload integrated together to form a system, encompasses much more than the design of the propulsion system and vehicle. The total cost includes the recurring cost of the process of integrating carriers, and payloads into the vehicle for each flight. The recurring cost of the integration of carrier/payloads systems is driven by the interaction of the vehicle. If the interaction can be well characterized and made to be very predictable for a range of payloads, or if it can be minimized then the cost of integrating a payload can be reduced significantly from today's levels. The Space Shuttle is very interactive with the payload. The interaction has been well characterized through finite element modeling and is reasonably predictable for a specific payload. Experience has shown, however, that the interaction is very manifest dependent, and small changes in one portion of a payload complement can change the interaction significantly in another portion. That is the affects of one on the other are such that if one or the other is changed slightly the environment at the interfaces can change significantly. To date the Shuttle has made in excess of one hundred flights. For each of these flights several iterations of dynamic analyses have been required in the development of each vehicle/carrier/payload system. The iterative analyses are needed because of the sensitivity of the interaction of the launch vehicle to the attached carrier/payload. The Multi Purpose Logistics Module (MPLM) is a carrier designed for flight in the Space Shuttle carrying a wide variation of cargo, supplies, and experiments to and from Space Station. Its integration process provides a unique area for improvement in the template in use today for transporting items to space. Discussion of the present MPLM integration analysis requirements and possible areas for improvement of the process are provided in the subject paper. Special emphasis is placed on reduction of requirements based on similarity of items being transported, and the use of carrier hardware for protection of the Shuttle Orbiter.

Shariett, Charles A.↗

CROSS: A GDSS for the Evaluation and Prioritization of Engineering Support Requests and Advanced Technology Projects at NASA

Objective evaluation and prioritization of engineering support requests (ESRs) is a difficult task at the Kennedy Space Center (KSC) Shuttle Project Engineering Office. The difficulty arises from the complexities inherent in the evaluation process and the lack of structured information. The purpose of this project is to implement the consensus ranking organizational support system (CROSS), a multiple criteria decision support system (DSS) developed at KSC that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. CROSS utilizes the analytic hierarchy process (AHP), subjective probabilities, entropy concept, and maximize agreement heuristic (MAH) to enhance the decision maker's intuition in evaluation ESRs. Some of the preliminary goals of the project are to: (1) revisit the structure of the ground systems working team (GWST) steering committee, (2) develop a template for ESR originators to provide more comple and consistent information to the GSWT steering committee members to eliminate the need for a facilitator, (3) develop an objective and structured process for the initial screening of ESRs, (4) extensive training of the stakeholders and the GWST steering committee to eliminate the need for a facilitator, (5) automate the process as much as possible, (6) create an environment to compile project success factor data on ESRs and move towards a disciplined system that could be used to address supportability threshold issues at the KSC, and (7) investigate the possibility of an organization-wide implementation of CROSS.

Tavana, Madjid↗

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗

Marine geodetic control for geoidal profile mapping across the Puerto Rican Trench

A marine geodetic control was established for the northern end of the geoidal profile mapping experiment across the Puerto Rican Trench by determining the three-dimensional geodetic coordinates of the four ocean-bottom mounted acoustic transponders. The data reduction techniques employed and analytical processes involved are described. Before applying the analytical techniques to the field data, they were tested with simulated data and proven to be effective in theory as well as in practice.

Fubara, D. M.↗