Search NASA⌕ Search

SEARCH · Search NASA

Results for “analytical process”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

Mars Geochemical Instrument (MarGI): An instrument for the analysis of the Martian surface and the search for evidence of life

The Mars Geochemical Instrument, MarGI, was developed to provide a comprehensive analysis of the rocks and surface material on Mars. The instrument combines Differential Thermal Analysis (DTA) with miniature Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) to identify minerals, the presence and state of water, and organic compounds. Miniature pyrolysis ovens are used to both, conduct DTA analysis of soil or crushed rocks samples, and pyrolyze the samples at temperatures up to 1000 degrees C for GC-IMS analysis of the released gases. This combination of analytical processes and techniques, which can characterize the mineralogy of the rocks and soil, and identify and quantify volatiles released during pyrolysis, has applications across a wide range of target sites including comets, planets, asteroids, and moons such as Titan and Europa. The MarGI analytical approach evolved from the Cometary Ice and Dust Experiment (CIDEX) selected to fly on the Comet Rendezvous Asteroid Flyby Mission (CRAF).

Kojiro, Daniel R.↗

Cost analysis of composite fan blade manufacturing processes

The relative manufacturing costs were estimated for large high technology fan blades prepared by advanced composite fabrication methods using seven candidate materials/process systems. These systems were identified as laminated resin matrix composite, filament wound resin matrix composite, superhybrid solid laminate, superhybrid spar/shell, metal matrix composite, metal matrix composite with a spar and shell, and hollow titanium. The costs were calculated utilizing analytical process models and all cost data are presented as normalized relative values where 100 was the cost of a conventionally forged solid titanium fan blade whose geometry corresponded to a size typical of 42 blades per disc. Four costs were calculated for each of the seven candidate systems to relate the variation of cost on blade size. Geometries typical of blade designs at 24, 30, 36 and 42 blades per disc were used. The impact of individual process yield factors on costs was also assessed as well as effects of process parameters, raw materials, labor rates and consumable items.

Stelson, T. S.↗

A graph signal processing‐based multiple model Kalman filter ( GSP‐MMKF ) tool for predictive analytics: An air separation unit process application

Abstract The industrial Air Separations Unit (ASU) is a complicated and tightly operated process. The use of dynamic process analytics is also a key element of safe and economic operation of these processes, with increasing focus on predictive analytics to take preemptive actions. With the availability of real‐time data from hundreds of sensors, the data analysis process should also consider the topology of the data, as seen in sensor networks. In this paper, a novel tool is presented that considers the complex connectivity patterns in the sensor network and uses local adaptive disturbance estimations to predict global network‐scale trends. The paper introduces the emerging field of Graph Signal Processing (GSP) and presents a rigorous derivation of the tool starting from the extraction of the sensor‐network (in a graph theoretical sense) from the data. This network, which is in the form of a matrix, is then used to derive a Kalman‐filter type of state‐space model driven by input disturbances. Multiple disturbance models (e.g., step, ramp, periodic) are included to allow the model to have different kinds of disturbance propagation. Each graph node (representing the sensors used) dynamically adapts to the most recent detected disturbance individually. These estimated disturbances are propagated to the global network using the graph. Modifications to ensure stability are also discussed. The fidelity of the tool is tested on certain downtime events and the paper concludes by discussing the advantages of the method and planned future improvements.

Ghosh, Sambit↗

Optimal Substrate Preheating Model for Thermal Spray Deposition of Thermosets onto Polymer Matrix Composites

High velocity oxy-fuel (HVOF) sprayed, functionally graded polyimide/WC-Co composite coatings on polymer matrix composites (PMC's) are being investigated for applications in turbine engine technologies. This requires that the polyimide, used as the matrix material, be fully crosslinked during deposition in order to maximize its engineering properties. The rapid heating and cooling nature of the HVOF spray process and the high heat flux through the coating into the substrate typically do not allow sufficient time at temperature for curing of the thermoset. It was hypothesized that external substrate preheating might enhance the deposition behavior and curing reaction during the thermal spraying of polyimide thermosets. A simple analytical process model for the deposition of thermosetting polyimide onto polymer matrix composites by HVOF thermal spray technology has been developed. The model incorporates various heat transfer mechanisms and enables surface temperature profiles of the coating to be simulated, primarily as a function of substrate preheating temperature. Four cases were modeled: (i) no substrate preheating; (ii) substrates electrically preheated from the rear; (iii) substrates preheated by hot air from the front face; and (iv) substrates electrically preheated from the rear and by hot air from the front.

Ivosevic, M.↗

International Space Station Potable Water Characterization for 2013

In this post-construction, operational phase of International Space Station (ISS) with an ever-increasing emphasis on its use as a test-bed for future exploration missions, the ISS crews continue to rely on water reclamation systems for the majority of their water needs. The onboard water supplies include US Segment potable water from humidity condensate and urine, Russian Segment potable water from condensate, and ground-supplied potable water, as reserve. In 2013, the cargo returned on the Soyuz 32-35 flights included archival potable water samples collected from Expeditions 34-37. The Water and Food Analytical Laboratory at the NASA Johnson Space Center continued its long-standing role of performing chemical analyses on ISS return water samples to verify compliance with potable water quality specifications. This paper presents and discusses the analytical results for potable water samples returned from Expeditions 34-37, including a comparison to ISS quality standards. During the summer of 2013, the U.S. Segment potable water experienced an anticipated temporary rise and fall in total organic carbon (TOC) content, as the result of organic contamination breaking through the water system's treatment process. Analytical results for the Expedition 36 archival samples returned on Soyuz 34 confirmed that dimethylsilanediol was once again the responsible contaminant, just as it was for comparable TOC rises in 2010 and 2012. Discussion herein includes the use of the in-flight Total Organic Carbon Analyzer (TOCA) as a key monitoring tool for tracking these TOC rises and scheduling appropriate remediation action.

Straub, John E. II↗

International Space Station Potable Water Characterization for 2013

In this post-construction, operational phase of International Space Station (ISS) with an ever-increasing emphasis on its use as a test-bed for future exploration missions, the ISS crews continue to rely on water reclamation systems for the majority of their water needs. The onboard water supplies include U.S. Segment potable water from humidity condensate and urine, Russian Segment potable water from condensate, and ground-supplied potable water, as reserve. In 2013, the cargo returned on the Soyuz 32-35 flights included archival potable water samples collected from Expeditions 34-37. The former Water and Food Analytical Laboratory (now Toxicology and Evironmental Chemistry Laboratory) at the NASA Johnson Space Center continued its long-standing role of performing chemical analyses on ISS return water samples to verify compliance with potable water quality specifications. This paper presents and discusses the analytical results for potable water samples returned from Expeditions 34-37, including a comparison to ISS quality standards. During the summer of 2013, the U.S. Segment potable water experienced a third temporary rise and fall in total organic carbon (TOC) content, as the result of organic contamination breaking through the water system's treatment process. Analytical results for the Expedition 36 archival samples returned on Soyuz 34 confirmed that dimethylsilanediol was once again the responsible contaminant, just as it was for the previous comparable TOC rises in 2010 and 2012. Discussion herein includes the use of the in-flight total organic carbon analyzer (TOCA) as a key monitoring tool for tracking these TOC rises and scheduling appropriate remediation.

Straub, John E., II↗

A Step-by-Step Protocol from METASPACE to Biological Interpretation

Mass spectrometry imaging (MSI) represents an exceptional tool for exploring complex biological systems spatially at the molecular level. However, due to its multidimensional nature and large-scale data output, it presents considerable challenges when it comes to extracting meaningful biological insights. Recent advancements, such as the METASPACE platform, have enabled researchers to efficiently process, annotate, and interpret MSI datasets by leveraging machine learning and cloud-based infrastructure. In this tutorial, we present a detailed and user-friendly R-pipeline designed to help METASPACE users navigate untargeted metabolomic annotations and transform them into practical insights about their biological systems. By combining METASPACE annotations with rapid R-based screening, this workflow not only streamlined the analytical process but also enhanced the understanding of spatial molecular distribution, especially for complex systems. Here, this easy-to-follow approach has the potential for applications in diagnostics, drug discovery, environmental and ecological processes, and more. We envision this pipeline to be particularly useful for newcomers to the field of MSI and

Moreno Pedraza, Abigail↗

Development of a continuous synthesis process for carbamazepine using validated in-line Raman spectroscopy and kinetic modelling for disturbance simulation

Mitigation of failure modes in the continuous synthesis (CS) of a drug substance (DS) has the potential to widen the adoption of continuous manufacturing (CM) technologies by the pharmaceutical industry. Here, this work demonstrates the development of a robust continuous process for the synthesis of carbamazepine (CBZ), an essential medicine as per the World Health Organization (WHO), facilitated by kinetic modelling and monitored by in-line Raman spectroscopy. Accurate kinetic modelling and the use of validated process analytical technology (PAT) models for quantitative measurement were found to play an important role in developing CS of drug substances. Kinetic data for the formation of CBZ from iminostilbene (ISB) were collected by batch reaction sampling and high-performance liquid chromatography (HPLC) analysis. A non-linear solver and iterative method was applied to determine two sets of Arrhenius parameters simultaneously for the reaction system by minimizing the standard error of the model fit. The start-up and dynamic equilibrium stages for the CS of CBZ using a continuous stirred tank reactor (CSTR) were modelled based on the batch kinetic data and employed to optimize conversion and simulate process disturbances. An in-line Raman spectroscopy method was successfully developed, validated, and integrated to determine the concentrations of CBZ and ISB within the operating range for the CS. The CS kinetic model was evaluated experimentally from startup to dynamic equilibrium over 10 residence times with monitoring by HPLC and in-line Raman spectroscopy. The developed kinetic model in tandem with in-line Raman spectroscopy successfully predicted disturbances due to changes in process variables and can serve as a useful tool in the future design of advanced process control strategies for the continuous synthesis of CBZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computer-Based Mathematics Instructions for Engineering Students

Almost every engineering course involves mathematics in one form or another. The analytical process of developing mathematical models is very important for engineering students. However, the computational process involved in the solution of some mathematical problems may be very tedious and time consuming. There is a significant amount of mathematical software such as Mathematica, Mathcad, and Maple designed to aid in the solution of these instructional problems. The use of these packages in classroom teaching can greatly enhance understanding, and save time. Integration of computer technology in mathematics classes, without de-emphasizing the traditional analytical aspects of teaching, has proven very successful and is becoming almost essential. Sample computer laboratory modules are developed for presentation in the classroom setting. This is accomplished through the use of overhead projectors linked to graphing calculators and computers. Model problems are carefully selected from different areas.

Khan, Mustaq A.↗

Protocols for Uranium Carbon Analysis

In 1998, MST-6 (now SIGMA) installed a Horiba EMIA-8200 Carbon/Sulfur analyzer to provide the ability to perform in-house chemical analysis on a variety of materials including uranium. While many of the results and procedures were detailed in program files, no compiled record of the overall analytic process was ever published. This retrospective utilizes existing logbooks, operator interviews, instrument manuals, and notes to catalog what is known about the past procedures and protocols for carbon analysis that were established and present the data informing those decisions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data Reliability in BIM and Performance Analytics: A Survey of Contemporary AECO Practice

As awareness around building energy consumption increases, practitioners are encouraged to consider performance aspects regarding the built environment more closely and find ways to improve its efficiency. Improvements in building information modeling (BIM) and building performance simulation (BPS) tools present opportunities to facilitate information communication with a wider range of stakeholders. The building sector can benefit from the integration of performance informatics; however, there has been limited success in utilizing available technologies that promote data integration and management in favor of enriching our knowledge and understanding of buildings as artifacts of information. This phenomenon was investigated by conducting a survey, together with a review of relevant literature, to depict the relevant challenges and opportunities for the architecture, engineering, construction, and owner-operated (AECO) industry, as it undergoes digital transformation, as well as the working practices that have formed around them. It is argued that the current tools available to practitioners do not support effective data serialization between design and analytics processes, affecting the collaboration between team members. Lastly, a series of functional goals are proposed to support a higher level of reliability in the ways information is mobilized, by rethinking the technologies and methods for organizing information systems.

42 ENGINEERING↗

Assessment of Existing OpenStudio Measures: Reviews, Interviews, and Future Developments

OpenStudio Measure development is continuously in progress and greatly propelled by the collaborative efforts within the building energy modeling community. To ensure the widespread adoption and benefit of OpenStudio Measures, developers must understand the current status of Measure development and the needs of OpenStudio Measure users. The first step involves a comprehensive review of existing content to prevent redundancy and gain insights into how OpenStudio Measures are used in the building energy modeling community. This knowledge can then be integrated into the Measure development process, and the expertise of practitioners and OpenStudio Measure users can be leveraged to shape future Measures. Numerous OpenStudio Measures have been created and shared on the Building Component Library (BCL). The BCL is an open-source repository housing various OpenStudio-related resources, including building component blocks, descriptive metadata, and Measures describing modifications to building energy models. The OpenStudio Measures in BCL encompass a wide range of energy conservation Measures from basic lighting power reduction to complex HVAC model transformation. They also enable users to generate customized reports and facilitate the integration of energy simulation with other analytical processes. This report presents review of 272 currently available OpenStudio Measures in BCL. The OpenStudio Measures were reviewed by category and subcategory. These Measures are summarized by their functionalities and keywords. To gain insights into how OpenStudio Measures are used in building energy modeling community, interviews were conducted. A total of 12 interview responses were collected from 6 individuals in the industry and 6 individuals in academia. The knowledge acquired from reviewing the existing Measures and interview results will be integrated into the Measure development process, and the expertise of practitioners and OpenStudio Measure users will be leveraged to shape future Measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation, Analysis, and Application of Internal Strain-Gage Balance Data

Experimental processes, analytical methods, and numerical algorithms are described that may be used to predict the forces and moments of an internal strain–gage balance during a wind tunnel test. First, the control volume model of a strain–gage balance and the concepts of load state, load space, and output space are introduced. These important abstractions provide a better understanding of fundamental characteristics of different balance load prediction approaches. Then, the description of strain–gage balance data and the definition of the primary bridge sensitivity are discussed. Afterwards, basic elements of the calibration of a typical six–component balance are reviewed. Two fundamentally different balance load prediction methods, the processing of check loads, and related topics are also discussed. Three real–world balance data examples are reviewed in great detail to illustrate typical analysis results for a variety of strain–gage balance designs. Finally, important observations are summarized and recommendations are provided. – Additional information and detailed mathematical derivations can be found in the appendices of the document. They include the following topics: balance terminology, definitions of important statistical metrics, balance axis system conventions, balance load transformations, the combined load diagram, electrical output format options, bi–directional output characteristics, determination of the natural zeros, derivation of two balance load prediction methods, description of two tare load iteration algorithms, modeling of balance temperature effects, basics of three–component moment balances, definition of the percent contribution, detection of linear and near–linear dependencies in balance calibration data, a regression model search algorithm, balance interactions, and other related information.

strain-gage balance↗

Evaluation, Analysis, and Application of Internal Strain-Gage Balance Data

Experimental processes, analytical methods, and numerical algorithms are described that may be used to predict the forces and moments of an internal strain-gage balance during a wind tunnel test. First, the control volume model of a strain-gage balance and the concepts of load state, load space, and output space are introduced. These important abstractions provide a better understanding of fundamental characteristics of different balance load prediction approaches. Then, the description of strain-gage balance data and the definition of the primary gage sensitivity is discussed. Afterwards, basic elements of the calibration of a typical six-component balance are reviewed. Two fundamentally different balance load prediction methods, the processing of check loads, and related topics are also discussed. Three real-world balance data examples are reviewed in great detail to illustrate typical analysis results for a variety of strain-gage balance designs. Finally, important observations are summarized and recommendations are provided. Additional information and detailed mathematical derivations can be found in the appendices of the document. They include the following topics: balance terminology, definitions of important statistical metrics, balance axis system conventions, balance load transformations, the combined load diagram, electrical output format options, bi-directional gage output characteristics, determination of the natural zeros, derivation of two balance load prediction methods, description of two tare load iteration algorithms, modeling of balance temperature effects, basics of three-component moment balances, definition of the percent contribution, detection of linear and near-linear dependencies in balance calibration data, a regression model term selection algorithm, and other related topics.

wind tunnel test↗

Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data

Orthogonal separations of data from high-resolution mass spectrometry can provide insight into sample composition and address challenges of complete annotation of molecules in untargeted metabolomics. “Molecular networks” (MNs), as used in the Global Natural Products Social Molecular Networking platform, are a prominent strategy for exploring and visualizing molecular relationships and improving annotation. MNs are mathematical graphs showing the relationships between measured multidimensional data features. MNs also show promise for using network science algorithms to automatically identify targets for annotation candidates and to dereplicate features associated with a single molecular identity. Here, this paper introduces “molecular hypernetworks” (MHNs) as more complex MN models able to natively represent multiway relationships among observations. Compared to MNs, MHNs can more parsimoniously represent the inherent complexity present among groups of observations, initially supporting improved exploratory data analysis and visualization. MHNs also promise to increase confidence in annotation propagation, for both human and analytical processing. We first illustrate MHNs with simple examples, and build them from liquid chromatography- and ion mobility spectrometry-separated MS data. We then describe a method to construct MHNs directly from existing MNs as their “clique reconstructions”, demonstrating their utility by comparing examples of previously published graph-based MNs to their respective MHNs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Avoid Procuring or Storing 2-Propanol in Opaque White, Clear Containers

One of the most important responsibilities chemical owners at Los Alamos National Laboratory (LANL) have is to ensure the safety of the chemicals they own. An important consideration is how chemicals react to their environment. In the case of 2-propanol, a common solvent found in research laboratories used often in manufacturing and analytical processes, it can develop peroxides with exposure to light. 2-Propanol is classified as a Group B (class 3) peroxide-forming solvent. However, there is a dearth of literature that summarizes the risks surrounding peroxide formation in 2-propanol (IPA), leading to a lack of awareness of these hazards in the chemistry community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

EDX ClaiMM

EDX ClaiMM is a centralized data & analytical platform designed to revolutionize U.S. critical minerals and materials (CMM) activities. By providing a robust digital infrastructure, ClaiMM will accelerate the combination, leveraging, and rapid utilization of vital data, advanced tools, and cutting-edge research advancements in CMM. This adaptive digital research hub connects the CMM community to essential knowledge products and offers access to interoperable datasets, databases, models, software, and tools from the National Energy Technology’s (NETL’s) Energy Data eXchange (EDX) and other authoritative sources, serving both public and private sectors. EDX ClaiMM delivers AI-informed solutions to address fundamental knowledge gaps and fosters the innovation of new techniques for enhanced characterization and recovery of CMMs within the U.S. By leveraging cloud-hosted, scalable digital infrastructure, ClaiMM meets public–private applied energy needs. It equips the CMM community with priority digital resources that harness on-site and cloud compute capabilities, enabling big data storage, advanced processing, analytics, and visualization.

Critical Materials; Critical Minerals; Rare Earth ↗

Boundary-layer receptivity due to distributed surface imperfections of a deterministic or random nature

Acoustic receptivity of a Blasius boundary layer in the presence of distributed surface irregularities is investigated analytically. It is shown that, out of the entire spatial spectrum of the surface irregularities, only a small band of Fourier components can lead to an efficient conversion of the acoustic input at any given frequency to an unstable eigenmode of the boundary layer flow. The location, and width, of this most receptive band of wavenumbers corresponds to a relative detuning of O(R sub l.b.(exp -3/8)) with respect to the lower-neutral instability wavenumber at the frequency under consideration, R sub l.b. being the Reynolds number based on a typical boundary-layer thickness at the lower branch of the neutral stability curve. Surface imperfections in the form of discrete mode waviness in this range of wavenumbers lead to initial instability amplitudes which are O(R sub l.b.(exp 3/8)) larger than those caused by a single, isolated roughness element. In contrast, irregularities with a continuous spatial spectrum produce much smaller instability amplitudes, even compared to the isolated case, since the increase due to the resonant nature of the response is more than that compensated for by the asymptotically small band-width of the receptivity process. Analytical expressions for the maximum possible instability amplitudes, as well as their expectation for an ensemble of statistically irregular surfaces with random phase distributions, are also presented.

Choudhari, Meelan↗