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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The 200 Gbps Challenge: Imagining HL-LHC analysis facilities

The IRIS-HEP software institute, as a contributor to the broader HEP Python ecosystem, is developing scalable analysis infrastructure and software tools to address the upcoming HL-LHC computing challenges with new approaches and paradigms, driven by our vision of what HL-LHC analysis will require. The institute uses a "Grand Challenge" format, constructing a series of increasingly large, complex, and realistic exercises to show the vision of HL-LHC analysis. Recently, the focus has been demonstrating the IRIS-HEP analysis infrastructure at scale and evaluating technology readiness for production. As a part of the Analysis Grand Challenge activities, the institute executed a "200 Gbps Challenge", aiming to show sustained data rates into the event processing of multiple analysis pipelines. The challenge integrated teams internal and external to the institute, including operations and facilities, analysis software tools, innovative data delivery and management services, and scalable analysis infrastructure. The challenge showcases the prototypes - including software, services, and facilities - built to process around 200 TB of data in both the CMS NanoAOD and ATLAS PHYSLITE data formats with test pipelines. The teams were able to sustain the 200 Gbps target across multiple pipelines. The pipelines focusing on event rate were able to process at over 30 MHz. These target rates are demanding; the activity revealed considerations for future testing at this scale and changes necessary for physicists to work at this scale in the future. The 200 Gbps Challenge has established a baseline on today's facilities, setting the stage for the next exercise at twice the scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Post-Flight Performance Analysis of Navigation and Advanced Guidance Algorithms on a Terrestrial Suborbital Rocket Flight

There is currently renewed interest in robotic and crewed landers for a return to the lunar surface. Advanced guidance and navigation algorithms are essential to accurately delivering cargo and crew safely to the moon successfully. This paper reports the overall performance of an integrated set of navigation and guidance algorithms flown on a terrestrial suborbital rocket up to an altitude of approximately 100km. The navigation algorithm consists of an onboard extended Kalman Filter (EKF) that ingests multiple sensor measurements, one of which is the output from a terrain relative navigation (TRN) algorithm that cross-references camera images to on-board satellite imagery to perform feature correlation within the camera image. The guidance algorithm solves for a 6-degree-of-freedom (DoF) optimal trajectory using a successive convexification method during powered descent. The altitude range as well as the landing dynamics experienced during this test flight are realistic for an extraterrestrial landing and provide an invaluable data set to gauge the current development of these landing algorithms in an effort to advance the overall software readiness levels (SRL). This paper will delve into different aspects of each algorithm and present an analysis of the in-flight performance of the algorithms. This flight was conducted under the National Aeronautics and Space Administration (NASA) Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project focused on technology advancement for landing applications.

Guidance↗
NASA NTRS2014

Venus High Temperature Atmospheric Dropsonde and Extreme-Environment Seismometer (HADES)

The atmospheric composition and geologic structure of Venus have been identified by the US National Research Council's Decadal Survey for Planetary Science as priority targets for scientific exploration, however the high temperature and pressure at the surface, along with the highly corrosive chemistry of the Venus atmosphere, present significant obstacles to spacecraft design that have severely limited past and proposed landed missions. Following the methodology of the NASA Innovative Advanced Concepts (NIAC) proposal regime and the Collaborative Modeling and Parametric Assessment of Space Systems (COMPASS) design protocol, this paper presents a conceptual study and initial feasibility analysis for a Discovery-class Venus lander capable of an extended-duration mission at ambient temperature and pressure, incorporating emerging technologies within the field of high temperature electronics in combination with novel configurations of proven, high Technology Readiness Level (TRL) systems. Radioisotope Thermal Power (RTG) systems and silicon carbide (SiC) communications and data handling are examined in detail, and various high-temperature instruments are proposed, including a seismometer and an advanced photodiode imager. The study combines this technological analysis with proposals for a descent instrument package and a relay orbiter to demonstrate the viability of an integrated atmospheric and in-situ geologic exploratory mission that differs from previous proposals by greatly reducing the mass, power requirements, and cost, while achieving important scientific goals.

HADES↗
NASA NTRS2013

An Overview of NASA's SubsoniC Research Aircraft Testbed (SCRAT)

National Aeronautics and Space Administration Dryden Flight Research Center acquired a Gulfstream III (GIII) aircraft to serve as a testbed for aeronautics flight research experiments. The aircraft is referred to as SCRAT, which stands for SubsoniC Research Aircraft Testbed. The aircraft’s mission is to perform aeronautics research; more specifically raising the Technology Readiness Level (TRL) of advanced technologies through flight demonstrations and gathering high-quality research data suitable for verifying the technologies, and validating design and analysis tools. The SCRAT has the ability to conduct a range of flight research experiments throughout a transport class aircraft’s flight envelope. Experiments ranging from flight-testing of a new aircraft system or sensor to those requiring structural and aerodynamic modifications to the aircraft can be accomplished. The aircraft has been modified to include an instrumentation system and sensors necessary to conduct flight research experiments along with a telemetry capability. An instrumentation power distribution system was installed to accommodate the instrumentation system and future experiments. An engineering simulation of the SCRAT has been developed to aid in integrating research experiments. A series of baseline aircraft characterization flights has been flown that gathered flight data to aid in developing and integrating future research experiments. This paper describes the SCRAT’s research systems and capabilities

aeronautics↗
NASA NTRS2013

An Overview of NASA's Subsonic Research Aircraft Testbed (SCRAT)

National Aeronautics and Space Administration Dryden Flight Research Center acquired a Gulfstream III (GIII) aircraft to serve as a testbed for aeronautics flight research experiments. The aircraft is referred to as SCRAT, which stands for SubsoniC Research Aircraft Testbed. The aircraft's mission is to perform aeronautics research; more specifically raising the Technology Readiness Level (TRL) of advanced technologies through flight demonstrations and gathering high-quality research data suitable for verifying the technologies, and validating design and analysis tools. The SCRAT has the ability to conduct a range of flight research experiments throughout a transport class aircraft's flight envelope. Experiments ranging from flight-testing of a new aircraft system or sensor to those requiring structural and aerodynamic modifications to the aircraft can be accomplished. The aircraft has been modified to include an instrumentation system and sensors necessary to conduct flight research experiments along with a telemetry capability. An instrumentation power distribution system was installed to accommodate the instrumentation system and future experiments. An engineering simulation of the SCRAT has been developed to aid in integrating research experiments. A series of baseline aircraft characterization flights has been flown that gathered flight data to aid in developing and integrating future research experiments. This paper describes the SCRAT's research systems and capabilities.

testbed↗
DOE OSTI2026

NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography

Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source. NeuDiff Agent takes instrument data through reduction, integration, refinement and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent coordinates established crystallographic tools under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing and controlled replay. The present benchmark is limited to structural crystallography for periodic structures; magnetic structure analysis and incommensurate or superspace refinement are outside the scope of the current workflow. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 min (manual) to 86.5 ± 4.7 to 94.4 ± 3.5 min (4.6–5.0× faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

Xiao, Zhongcan [ORNL] (ORCID:0000000220761961)↗
NASA NTRS1992

Communications system evolutionary scenarios for Martian SEI support

In the Space Exploration Initiative (SEI) mission scenarios, expanding human presence is the primary driver for high data rate Mars-Earth communications. To support an expanding human presence, the data rate requirement will be gradual, following the phased implementation over time of the evolving SEI mission. Similarly, the growth and evolution of the space communications infrastructure to serve this requirement will also be gradual to efficiently exploit the useful life of the installed communications infrastructure and to ensure backward compatibility with long-term users. In work conducted over the past year, a number of alternatives for supporting high data rate Mars-Earth communications have been analyzed with respect to their compatibility with gradual evolution of the space communications infrastructure. The alternatives include RF, millimeter wave (MMW), and optical implementations, and incorporate both surface and space-based relay terminals in the Mars and Earth regions. Each alternative is evaluated with respect to its ability to efficiently meet a projected growth in data rate over time, its technology readiness, and its capability to satisfy the key conditions and constraints imposed by evolutionary transition. As a result of this analysis, a set of attractive alternative communications architectures have been identified and described, and a road map is developed that illustrates the most rational and beneficial evolutionary paths for the communications infrastructure.

Kwong, Paulman W.↗
NASA NTRSDate not supplied

Multidimensional Data Aggregation in the Cloud with Application to Geostationary Satellite-based Air Quality Monitoring

Scientists use satellite data for studying Earth's systems, and the remote sensing data that these satellites collect are typically separated into files of a size small enough for efficient network transfer and storage. However, researchers usually prefer to analyze the data based on real-world dimensions like time, space, or elevation. To help with this, NASA's Atmospheric Science Data Center (ASDC) developed a new cloud-based tool that combines these smaller data chunks into larger, more useful datasets. The tool works on Network Common Data Form (netCDF4) and some HDF5 formatted files, and it is available as a service in NASA's Earthdata Cloud. In this presentation, we showcase this service using data from the Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument. By combining TEMPO's continuous observations over time, we create longer and more informative analysis-ready time series to facilitate the study of air quality patterns. Insights gained will provide a more comprehensive understanding of pollution sources, transport patterns, and their effects on the environment and human health.

Daniel Kaufman↗
NASA NTRS2017

Estimating the Relative Water Content of Leaves in a Cotton Canopy

Remotely sensing plant canopy water status remains a long-term goal of remote sensing research. Established approaches to estimating canopy water status the Crop Water Stress Index, the Water Deficit Index and the Equivalent Water Thickness involve measurements in the thermal or reflective infrared. Here we report plant water status estimates based upon analysis of polarized visible imagery of a cotton canopy measured by ground Multi-Spectral Polarization Imager (MSPI). Such estimators potentially provide access to the plant hydrological photochemistry that manifests scattering and absorption effects in the visible spectral region.Twice during one day, +- 3 hours from solar noon, we collected polarized imagery and relative water content data on a cotton test plot located at the Arid Land Agricultural Research Center, United States Department of Agriculture, Maricopa, AZ. The test plot, a small portion of a large cotton field, contained stressed plants ready for irrigation. The evening prior to data collection we irrigated several rows of plants within the test plot. Thus, ground MSPI imagery from both morning and afternoon included cotton plants with a range of water statuses. Data analysis includes classifying the polarized imagery into sunlit reflecting, sunlit transmitting, shaded foliage and bare soil. We estimate the leaf surface reflection and interior reflection based upon the per pixel polarization and sunview directions. We compare our cotton results with our prior polarization results for corn and soybean leaves measured in the lab and corn leaves measured in the field.

Cotton Canopy↗
DOE OSTI2024

Multicriteria-Based Selection of Microalgae Biorefineries: Biomass Composition Defines the Most Suitable Product Portfolios

The supply of microalgae-derived biofuels and bioproducts will be vital in a global-scale bioeconomy. As the diversity of microalgae strains and their compositional plasticity may yield a wide array of products of market interest, the design of effective biorefineries is a central aspect in the path to making microalgae-based products available in the market. In this way, the conversion of microalgae biomass should be planned to employ mature technologies, while maximizing economic and environmental benefits obtained from a diverse product portfolio. This study applied sequential, hybrid Multicriteria Decision Analyses (MCDA) to aid the decision-making process of outlining the most suitable biorefining pathways for specific compositional profiles. For this, the methodology simultaneously considered multiple technical, economic, and environmental criteria, such as market aspects for the main algae-derived products, potential reduction in greenhouse gas (GHG) emissions provided by the biobased alternatives, and technology readiness level of conversion routes, among others. The framework was tested using productivity and compositional data for 13 high-productivity summer strains cultivated under varying nutrient availability. The analysis pointed to compositional profile being a key driver in defining the core biorefining strategy of algae biomass, with lipid-to-carbohydrate ratios higher than roughly 1 warranting the preferential processing of lipids into hydrocarbon fuels with the remainder of the algae biomass compounds being sent to higher-value applications, such as carboxylic acids and renewable thermoplastic substitutes. An in-depth process simulation, techno-economic assessment (TEA), and life-cycle analysis (LCA) effort was carried out as a closing step to corroborate the results stemming from the proposed framework. This study validates the use of MCDAs as a screening method prior to implementing more time-consuming analysis techniques and makes a compelling case for this approach as a product selection tool on a wide range of algae species, thus helping establish species-agnostic (but composition-driven) biorefineries.

biofuels↗
DOE OSTI2020

The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes

Abstract For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org and KBase.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Advancing Supersonic Retropropulsion Using Mars-Relevant Flight Data: An Overview

Advanced robotic and human missions to Mars require landed masses well in excess of current capabilities. One approach to safely land these large payloads on the Martian surface is to extend the propulsive capability currently required during subsonic descent to supersonic initiation velocities. However, until recently, no rocket engine had ever been fired into an opposing supersonic freestream. In September 2013, SpaceX performed the first supersonic retropropulsion (SRP) maneuver to decelerate the entry of the first stage of their Falcon 9 rocket. Since that flight, SpaceX has continued to perform SRP for the reentry of their vehicle first stage, having completed multiple SRP events in Mars-relevant conditions in July 2017. In FY 2014, NASA and SpaceX formed a three-year public-private partnership centered upon SRP data analysis. These activities focused on flight reconstruction, CFD analysis, a visual and infrared imagery campaign, and Mars EDL design analysis. This paper provides an overview of these activities undertaken to advance the technology readiness of Mars SRP.

Braun, Robert D.↗
NASA NTRS2017

Advancing Supersonic Retropropulsion Using Mars-Relevant Flight Data: An Overview

Advanced robotic and human missions to Mars require landed masses well in excess of current capabilities. One approach to safely land these large payloads on the Martian surface is to extend the propulsive capability currently required during subsonic descent to supersonic initiation velocities. However, until recently, no rocket engine had ever been fired into an opposing supersonic freestream. In September 2013, SpaceX performed the first supersonic retropropulsion (SRP) maneuver to decelerate the entry of the first stage of their Falcon 9 rocket. Since that flight, SpaceX has continued to perform SRP for the reentry of their vehicle first stage, having completed multiple SRP events in Mars-relevant conditions in July 2017. In FY 2014, NASA and SpaceX formed a three-year public-private partnership centered upon SRP data analysis. These activities focused on flight reconstruction, CFD analysis, a visual and infrared imagery campaign, and Mars EDL design analysis. This paper provides an overview of these activities undertaken to advance the technology readiness of Mars SRP.

Braun, Robert D.↗
NASA NTRS2004

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗
NASA NTRS2013

Coordinated Analyses of Antarctic Sediments as Mars Analog Materials Using Reflectance Spectroscopy and Current Flight-Like Instruments for CheMin, SAM and MOMA

Coordinated analyses of mineralogy and chemistry of sediments from the Antarctic Dry Valleys illustrate how data obtained using flight-ready technology of current NASA and ESA missions can be combined for greater understanding of the samples. Mineralogy was measured by X-ray diffraction (XRD) and visible/ near-infrared (VNIR) reflectance spectroscopy. Chemical analyses utilized a quadrupole mass spectrometer (QMS) to perform pyrolysis-evolved gas analysis (EGA) and gas chromatography-mass spectrometry (GC/MS) both with and without derivatization, as well as laser desorption-mass spectrometry (LD/MS) techniques. These analyses are designed to demonstrate some of the capabilities of near-term landed Mars missions, to provide ground truthing of VNIR reflectance data acquired from orbit by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on MRO and to provide detection limits for surface- operated instruments: the Chemistry and Mineralogy (CheMin) and Sample Analysis at Mars (SAM) instrument suites onboard Mars Science Laboratory (MSL) and the Mars Organic Molecule Analyzer (MOMA) onboard ExoMars-2018. The new data from this study are compared with previous analyses of the sediments performed with other techniques. Tremolite was found in the oxic region samples for the first time using the CheMin-like XRD instrument. The NIR spectral features of tremolite are consistent with those observed in these samples. Although the tremolite bands are weak in spectra of these samples, spectral features near 2.32 and 2.39 micrometers could be detected by CRISM if tremolite is present on the martian surface. Allophane was found to be a good match to weak NIR features at 1.37-1.41, 1.92, and 2.19 micrometers in spectra of the oxic region sediments and is a common component of immature volcanic soils. Biogenic methane was found to be associated with calcite in the oxic region samples by the SAM/EGA instrument and a phosphoric acid derivative was found in the anoxic region sample using the SAM/MTBSTFA technique.

Mars↗
DOE OSTI2026

The high level trigger and express data production at STAR

To meet the demands of the Beam Energy Scan phase-II (BES-II) program, the STAR experiment at the Relativistic Heavy Ion Collider (RHIC) developed a dual real-time framework consisting of a High Level Trigger (HLT) and an Express Data Production system (xProduction). The HLT operates online within the Data Acquisition (DAQ) chain on a dedicated multi-core CPU cluster with the option to offload compute-intensive kernels to Xeon Phi coprocessors. It uses parallelized algorithms, such as the Cellular Automaton (CA) Track Finder, to perform rapid tracking, vertexing, and event filtering. This allows it to select events of interest in real time and provide immediate feedback on detector and beam conditions. In contrast, the xProduction workflow runs concurrently and independently of the DAQ loop. It applies near offline-quality calibration and reconstruction within hours of data collection. The xProduction input is the express data stream, whose content can be enriched by HLT trigger/priority selections under DAQ/HLT resource constraints, and it uses the STAR calibration/conditions framework, incorporating online calibration/QA information when available. This enables early preliminary physics analysis, including the reconstruction of rare signals, such as hyperons and hypernuclei. It also provides collaboration-wide access to analysis-ready datasets. Together, the HLT and xProduction systems form a complementary architecture: the HLT performs online event selection while the xProduction chain delivers high-quality results within a short amount of time. This integrated framework has enabled the prompt reconstruction of the $^5_Λ$ He hypernucleus with high statistical significance and the efficient processing of hundreds of millions of heavy-ion collision events. In conclusion, its demonstrated scalability and robustness establish a model for future high-luminosity experiments requiring both online event filtering and rapid access to analysis-quality data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1992

A new unsteady mixing model to predict NO(x) production during rapid mixing in a dual-stage combustor

An advanced gas turbine engine to power supersonic transport aircraft is currently under study. In addition to high combustion efficiency requirements, environmental concerns have placed stringent restrictions on the pollutant emissions from these engines. A combustor design with the potential for minimizing pollutants such as NO(x) emissions is undergoing experimental evaluation. A major technical issue in the design of this combustor is how to rapidly mix the hot, fuel-rich primary zone product with the secondary diluent air to obtain a fuel-lean mixture for combustion in the second stage. Numerical predictions using steady-state methods cannot account for the unsteady phenomena in the mixing region. Therefore, to evaluate the effect of unsteady mixing and combustion processes, a novel unsteady mixing model is demonstrated here. This model has been used to study multispecies mixing as well as propane-air and hydrogen-air jet nonpremixed flames, and has been used to predict NO(x) production in the mixing region. Comparison with available experimental data show good agreement, thereby providing validation of the mixing model. With this demonstration, this mixing model is ready to be implemented in conjunction with steady-state prediction methods and provide an improved engineering design analysis tool.

Menon, Suresh↗