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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Space Mission Concept Development Using Concept Maturity Levels

Over the past five years, pre-project formulation experts at the Jet Propulsion Laboratory (JPL) has developed and implemented a method for measuring and communicating the maturity of space mission concepts. Mission concept development teams use this method, and associated tools, prior to concepts entering their Formulation Phases (Phase A/B). The organizing structure is Concept Maturity Level (CML), which is a classification system for characterizing the various levels of a concept's maturity. The key strength of CMLs is the ability to evolve mission concepts guided by an incremental set of assessment needs. The CML definitions have been expanded into a matrix form to identify the breadth and depth of analysis needed for a concept to reach a specific level of maturity. This matrix enables improved assessment and communication by addressing the fundamental dimensions (e.g., science objectives, mission design, technical risk, project organization, cost, export compliance, etc.) associated with mission concept evolution. JPL's collaborative engineering, dedicated concept development, and proposal teams all use these and other CML-appropriate design tools to advance their mission concept designs. This paper focuses on mission concept's early Pre-Phase A represented by CMLs 1- 4. The scope was limited due to the fact that CMLs 5 and 6 are already well defined based on the requirements documented in specific Announcement of Opportunities (AO) and Concept Study Report (CSR) guidelines, respectively, for competitive missions; and by NASA's Procedural Requirements NPR 7120.5E document for Projects in their Formulation Phase.

Concept Maturity Levels (CMLs)↗
NASA NTRS2023

Interpretation of Probabilistic Surface Ozone Forecasts: A Case Study for Philadelphia

The use of probabilistic forecasting has been growing in a variety of disciplines because of its potential to emphasize the degree of uncertainty inherent in a prediction. Interpretation of probabilistic forecasts, however, is oftentimes difficult, deterring users who may benefit from such forecasts. To encourage broader use of probabilistic forecasts in the field of air quality, a process for interpreting forecasts from a statistical probabilistic air quality surface ozone model [the Regression in Self Organizing Map (REGiS)] is demonstrated. Four procedures to convert probabilistic to deterministic forecasts are explored for the Philadelphia, Pennsylvania, metropolitan area. These procedures calibrate the predicted probability of daily maximum 8-h-average ozone exceeding a standard value by 1) estimating climatological relative frequency, 2) establishing a probability of an exceedance threshold as 50%, 3) maximizing the threat score, and 4) determining the unit bias ratio. REGiS is trained using 2000–11 ozone-season (1 May–30 September) data, calibrated using 2012–14 data, and evaluated using 2015–18 data. Assessment of the calibration data with the Pierce skill score suggests an exceedance threshold based on climatological relative frequency for the conversion from probabilistic to deterministic forecasts. Calibrated REGiS generally compares well to predictions from the U.S. national air quality model and operational “expert” forecasts over the evaluation period. For other probabilistic models and situations, different procedures of converting probabilistic to deterministic forecasts may be more beneficial. The methods presented in this paper represent an approach for operational air quality forecasters seeking to use probabilistic model output to support forecasts designed to protect public health.

Nikolay Balashov↗
NASA NTRSDate not supplied

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or aerial wildfire operations reports to better understand the risks present. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement. These applications can benefit from the use of state-of-the-art natural language processing techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of adaptation of NLP tools to the aviation domain by fine-tuning transformer based models using aviation data sets. In 2018, a novel language model based on neural units (also called transformers) was created and became known as “Bidirectional Encoder Representations from Transformers” or BERT. This architecture combined with large amounts of English training data and innovative semi-supervised training tasks set the standard for what would later emerge as Large Language Models. The performance of these models was further improved by hyperparameter tuning and refinement of the semi-supervised training task and resulted in “Robustly Optimized BERT Pre-training Approach through hyperparameter tuning” or RoBERTa models. These pre-trained Large Language Models proved to be useful for a wide variety of natural language processing tasks such as text classification and question answering through a process called fine-tuning. The transformer architecture with pre-trained weights served as the basis with the last few layers replaced with layers fine-tuned to perform a new task e.g., a layer that provides a label for the entire input text. This process of fine-tuning can also be used to adapt the models to new domains; e.g., BioBERT started with the pre-trained BERT model and was completed by additional fine-tuning and training on biomedical documents. Transformer-based architectures can also be used to create rich representations of text called embeddings which can serve as the input to other machine learning models. This allows simpler algorithms such as logistic regression to use context-rich representations of the text while still remaining quick to train and evaluate. In the world of aviation, there is a growing demand for natural language processing and understanding but the domain presents unique challenges. Due to the technical content (and specialized language) of most aviation documents, fine-tuning pre-trained Large Language Models to specific tasks has not met the benchmark on natural language processing tasks set by simpler models trained from scratch on the data. To address this deficiency, this paper evaluates the improvements from fine-tuning a Large Language Model on a large set of aviation documents using the original semi-supervised training tasks before performing specific natural language tasks. In fine-tuning, a domain-specific dataset is used on the original training task but with the pre-trained Large Language Model instead of starting from a random initialization. This approach allows the model to be adapted to the specific domain language without discarding the information gained from training on general English data. This paper utilized two major dataset types to train and assess the RoBERTa fine-tuning performance. The first are 7,057 Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the semi-supervised fine-tuning. The second type is the 494 document classification labels to be used for evaluation. This down-stream evaluation aims to show the performance of the fine-tuned model, better understand how much data is needed for an effective fine-tuning, and how fine-tuning can be adapted for different applications in-the domain. After semi-supervised training, evaluation begins by encoding the documents for classification using the fine-tuned RoBERTa model. Then a logistic regression classifier is trained to label the document type and compared against our ground truth labels. This currently leads to a 82.8% accuracy on 10-fold cross validation showing improvement over baseline RoBERTa which achieved 81.0%. We plan to measure the improvements on additional tasks and it is expected that these improvements will lead to more robust models that can tackle the natural language processing challenges present in aviation datasets.

ATM↗
NASA NTRS2023

The IAU Recommended Photometric System for Ultraviolet Astronomy

In the current era when access to space is becoming easier and at a lower cost thanks to the standardised cubesat technology, numerous missions are expected to be launched to observe, particularly, at ultraviolet wavelengths. Given the reduced dimensions of the telescope that a cubesat can carry, most of these missions will be focused on photometric surveys of a reduced sample of targets of interest, and therefore each mission will define their own photometric bands according to their scientific objectives and orbital constraints. However, in order to provide a coherent view of the ultraviolet sky, the data should be post-processed under a common framework. In 2017, the IAU working group on ultraviolet astronomy identified the need to define such a common framework for the upcoming ultraviolet missions, and coordinated the definition of a standard set of photometric bands that could serve for homogenizing the current and future data. This paper presents the procedure adopted by the working group for the definition of the standard photometric system, that was approved by the IAU during the General Assembly Business Sessions held in August, 2021. The photometric system consists of seven bands, denoted as UV1-UV7, all included in the range 115 - 400 nm. Some of these bands are based on existing filters, while others have been defined as theoretical bands with constant throughput. This system is to be regarded as a set of synthetic bands for post-processing the data of any mission, and an example of its application to the SPARCS cubesat is also included. The photometric bands are publicly available and can be downloaded from https://www.nuva.eu/uv-photometry/.

Ultraviolet: ISM↗
DOE OSTI2018

Integrated System of Thermal/Dimensional Analysis for Quality Control of Metallic Melt and Ductile Iron Casting Solidification

The main objective of the present work is to introduce a specific experimental instrument and technique for simultaneously evaluating cooling curves and expansion or contraction of cast metals during solidification. Contraction/expansion analysis illustrates the solidification parameters progression, according to the molten cast iron characteristics, which are dependent on the melting procedure and applied metallurgical treatments, mold media rigidity and thermal behavior [heat transfer parameters]. The first part of the paper summarizes the performance of this two-mold device. Its function is illustrated by representative shrinkage tendency results in ductile cast iron as affected by mold rigidity (green sand and furan resin sand molds) and inoculant type (FeSi-based alloys), published in part previously. The second part of the paper illustrates an application of this equipment adapted for commercial foundry use. It conducts thermal analysis and volume change measurements in a single ceramic cup so that mold media as well as solidification conditions are constants, with cast iron quality as the variable. Experiments compared gray and ductile cast iron solidification patterns. Gray iron castings are characterized by higher undercooling at the beginning and at the end of solidification and lower graphitic expansion. Typically, ductile cast iron exhibits higher graphitic, initial expansion, conducive for shrinkage formation in soft molds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A universal variational quantum eigensolver for non-Hermitian systems

Abstract Many quantum algorithms are developed to evaluate eigenvalues for Hermitian matrices. However, few practical approach exists for the eigenanalysis of non-Hermintian ones, such as arising from modern power systems. The main difficulty lies in the fact that, as the eigenvector matrix of a general matrix can be non-unitary, solving a general eigenvalue problem is inherently incompatible with existing unitary-gate-based quantum methods. To fill this gap, this paper introduces a Variational Quantum Universal Eigensolver (VQUE), which is deployable on noisy intermediate scale quantum computers. Our new contributions include: (1) The first universal variational quantum algorithm capable of evaluating the eigenvalues of non-Hermitian matrices—Inspired by Schur’s triangularization theory, VQUE unitarizes the eigenvalue problem to a procedure of searching unitary transformation matrices via quantum devices; (2) A Quantum Process Snapshot technique is devised to make VQUE maintain the potential quantum advantage inherited from the original variational quantum eigensolver—With additional $$O(log_{2}{N})$$ O ( l o g 2 N ) quantum gates, this method efficiently identifies whether a unitary operator is triangular with respect to a given basis; (3) Successful deployment and validation of VQUE on a real noisy quantum computer, which demonstrates the algorithm’s feasibility. We also undertake a comprehensive parametric study to validate VQUE’s scalability, generality, and performance in realistic applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Measurement of the 252 Cf ⁢(sf) prompt fission neutron spectrum utilizing 12 C ⁡(𝑛, 𝑛) and 9 Be ⁢(𝑛, 𝑛) neutron scattering reference measurements

The 252 Cf spontaneous fission (sf), prompt fission neutron spectrum (PFNS) is a fundamental quantity for nuclear physics measurements of neutron-emitting reactions. This energy distribution of neutrons emitted from fission has been considered a neutron data standard for decades and has been utilized as a reference for neutron detection efficiency, validation of Monte Carlo simulations, benchmarking of dosimetry standards, and more. A significant portion of the global collection of nuclear data on neutron-induced reactions is correlated with the 252 Cf ⁢(sf) PFNS. Despite the reliance on this quantity by the nuclear physics community, the historical collection of 252 Cf PFNS measurements display systematic disagreements that are not understood or easily explained. These experimental discrepancies could potentially bias the 252 Cf PFNS Standard evaluation. On top of this, these past experiments frequently employed correlated experimental measurement or analysis methods. The artificial intelligence (AI)/machine learning (ML)-informed californium chi-nuclear data experiment (AIACHNE) project was formed to (a) investigate these discrepancies utilizing AI/ML methods to identify outlying regions of literature data, assign these regions to features of the experiment itself, and perform an improved evaluation of the 252 Cf PFNS and (b) perform a new experimental measurement of this quantity designed to improve upon the existing literature database. Here, in this work, we report on the AIACHNE 252 Cf PFNS experiment utilizing a new analysis method uncorrelated with all previous measurements: neutron efficiency determinations based on elastic neutron scattering on 12 C and 9 Be . This new method provides an independent test of the existing literature data and evaluation of the 252 Cf ⁢(sf) PFNS. The method is described with detailed covariance quantification procedures, as well as a direct discussion of the sources of uncertainty described as requirements in the “Templates” series of papers. The 252 Cf ⁢(sf) PFNS reported in this work agrees well with the overall shape of the existing standard PFNS evaluation as well as many literature measurements, thus verifying the current evaluation utilizing new techniques. However, the results suggest that there are deficiencies in the angle-differential 12 C and 9 Be ⁢(𝑛, 𝑛) evaluated nuclear data, which produce unphysical structures in the reported result. While these structures are relatively minor, they become obvious because of the high statistical precision of the data and the expected smooth continuity of the 252 Cf ⁢(sf) PFNS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1988

Radiometric calibration analysis of SIR-B imagery

The second flight of the NASA Spaceborne Imaging Radar (SIR-B) collected nearly 8 hours of digital synthetic-aperture radar (SAR) data of the earth's surface. This paper analyzes the performance of the SAR to determine the accuracy of the relative radiometric calibration of these data. Procedures are presented for deriving accuracy estimates as well as limitations under which these estimates are valid. The impact on calibration of an RF breakdown in the primary antenna feed system cable is evaluated. An analysis of the platform stability based on the SAR echo data is also presented in conjunction with its resultant effect on the calibration accuracy. Finally, numerical error bounds are derived with guidelines on their utilization.

Wall, Stephen D.↗
NASA NTRS1991

A method for the retrieval of atomic oxygen density and temperature profiles from ground-based measurements of the O(+)(2D-2P) 7320 A twilight airglow

This paper describes a technique for extracting thermospheric profiles of the atomic-oxygen density and temperature, using ground-based measurements of the O(+)(2D-2P) doublet at 7320 and 7330 A in the twilight airglow. In this method, a local photochemical model is used to calculate the 7320-A intensity; the method also utilizes an iterative inversion procedure based on the Levenberg-Marquardt method described by Press et al. (1986). The results demonstrate that, if the measurements are only limited by errors due to Poisson noise, the altitude profiles of neutral temperature and atomic oxygen concentration can be determined accurately using currently available spectrometers.

Fennelly, J. A.↗
NASA NTRS1995

Optimal domain decomposition strategies

The primary interest of the authors is in the area of grid generation, in particular, optimal domain decomposition about realistic configurations. A grid generation procedure with optimal blocking strategies has been developed to generate multi-block grids for a circular-to-rectangular transition duct. The focus of this study is the domain decomposition which optimizes solution algorithm/block compatibility based on geometrical complexities as well as the physical characteristics of flow field. The progress realized in this study is summarized in this paper.

Yoon, Yonghyun↗
NASA NTRS1997

Designing to Control Flight Crew Errors

It is widely accepted that human error is a major contributing factor in aircraft accidents. There has been a significant amount of research in why these errors occurred, and many reports state that the design of flight deck can actually dispose humans to err. This research has led to the call for changes in design according to human factors and human-centered principles. The National Aeronautics and Space Administration's (NASA) Langley Research Center has initiated an effort to design a human-centered flight deck from a clean slate (i.e., without constraints of existing designs.) The effort will be based on recent research in human-centered design philosophy and mission management categories. This design will match the human's model of the mission and function of the aircraft to reduce unnatural or non-intuitive interfaces. The product of this effort will be a flight deck design description, including training and procedures, and a cross reference or paper trail back to design hypotheses, and an evaluation of the design. The present paper will discuss the philosophy, process, and status of this design effort.

Schutte, Paul C.↗
NASA NTRS2012

NASA's ATM Technology Demonstration-1: Integrated Concept of Arrival Operations

This paper describes operations and procedures envisioned for NASA s Air Traffic Management (ATM) Technology Demonstration #1 (ATD-1). The ATD-1 Concept of Operations (ConOps) demonstration will integrate three NASA technologies to achieve high throughput, fuel-efficient arrival operations into busy terminal airspace. They are Traffic Management Advisor with Terminal Metering (TMA-TM) for precise time-based schedules to the runway and points within the terminal area, Controller-Managed Spacing (CMS) decision support tools for terminal controllers to better manage aircraft delay using speed control, and Flight deck Interval Management (FIM) avionics and flight crew procedures to conduct airborne spacing operations. The ATD-1 concept provides de-conflicted and efficient operations of multiple arrival streams of aircraft, passing through multiple merge points, from top-of-descent (TOD) to touchdown. It also enables aircraft to conduct Optimized Profile Descents (OPDs) from en route altitude to the runway, using primarily speed control to maintain separation and schedule. The ATD-1 project is currently addressing the challenges of integrating the three technologies, and implantation into an operational environment. Goals of the ATD-1 demonstration include increasing the throughput of high-density airports, reducing controller workload, increasing efficiency of arrival operations and the frequency of trajectory-based operations, and promoting aircraft ADS-B equipage.

Baxley, Brian T.↗
NASA NTRS2014

Sharepoint Team Site Configuration

The Data Mining project seeks to bring the capability of data visualization to NASA anomaly and problem reporting systems for the purpose of improving data trending, evaluations, and analyses. Currently NASA systems are tailored to meet the specific needs of its organizations. This tailoring has led to a variety of nomenclatures and levels of annotation for procedures, parts and anomalies making difficult the realization of the common causes for anomalies. Making significant observations and realizing the connection between these causes without a common way to view data is difficult to impossible. The Data Mining project is in its early stages of presenting a common visualization of normalized data through a web based portal. In this paper I detail what I have learned and what I have accomplished during my time as an intern toward the purpose of creating the project portal. I have gone through an iterative process of familiarization with the project and its goals, site design, research, modification and review on the road to creating a common method and location to view the visualized data created under this project.

iss↗
NASA NTRSDate not supplied

Development of Optical Step Height Measurement Capability for the BOLT Flight Vehicle

This paper presents details on the development of testing procedures to evaluate two different optical step height sensors that were intended for use on the first and second Boundary Layer Transition (BOLT and BOLT II) flight vehicle as well as other flight vehicles. The accurate and precise measurement of step height at the interface of different sections of a flight vehicle is important, as small changes in the step height (in some instances < 10 microns) at such locations can have a significant influence on the development of a boundary layer over the outer surface of the vehicle, which in turn can significantly impact aeroheating (among other things). In this paper, testing procedures have been developed, and test hardware assembled, to determine the capabilities of two optical step height sensor candidates. The first candidate is a miniaturized camera sensor that would be embedded into the body of a flight vehicle and would image the interface between two sections of that vehicle. The second candidate is a small fiber-based optical sensor that would also be embedded into the body of the flight vehicle, but projects light onto the interface between two sections of the flight vehicle, and then monitors any reflected/scattered light from that interface. Preliminary data from these two sensor candidates are presented, and a discussion of improvements that will be made in the testing procedures and to the test hardware is provided.

Brett F Bathel↗
DOE OSTI2021

Cyber Threat Assessment Methodology for Autonomous and Remote Operations for Advanced Reactors (Conference Presentation)

The next generation of Advanced Reactors include planned capabilities for both Autonomous (operating without human interaction for a set period-of-time) and Remote (operating with human interaction from a separate physical location) Operations. Existing Nuclear Reactor architectures include a set of safety and security constraints tightly coupled with personnel policies and procedures. As Advanced Reactors are fielded with these new Autonomous and Remote operational capabilities, the architectures and associated infrastructure services and components will perceivably expand the overall attack surface and risk calculations with regards to safe and secure operations. This paper is part of an FY21 work program focused on ensuring Advanced Reactor designs are informed with threat-based guidance on design and operation of Secure Architectures with a specific focus on the deployment of Autonomous Systems in support of Advanced Reactor Operations. The next phase of this research program is to complement produce a methodology for assessment of the cyber threat against these architectures as well as a catalogue of Use Cases to support the Advanced Reactor community in their implementation of Autonomous and Remote Operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

CYRANO3 the EDF fuel code performance: Global overview and recent developments on MOX fuel

CYRANO3 is the thermal mechanical industrial code developed and used by EDF to simulate the nuclear fuel rod performance in pile, and during the disposal storage period as well. This code has already been used successfully for the last ten years by the EDF engineering teams in justifying the overall reloading options covering various fuels: UO{sub 2}, UO{sub 2} + gadolinium, MOX, UO{sub 2} plus additives, and various cladding as well proposed by the nuclear fuel suppliers. Its particularity is related to a construction around a standard one-dimensional thermal and mechanical finite elements kernel with an appropriate architecture to plug in any new functionalities or models. Since the beginning it is developed as a module able integrating within a core calculation chain. Other constrain is to always guaranty a running time consistent with the calculation of a core within a reasonable time. The objective is to provide the EDF designers with a convivial and qualified code, with robust algorithms and able to quickly evolve with computer performances. Algorithms are able to account for adiabatic transients and are robust enough to avoid any undesirable overflows. The permanent challenge is indeed to provide with the more descriptive simulations not degrading to much the running time. Developments are obviously performed within the strict Quality Insurance rules. The code is then associated to a large documentation base, including model specification, realization, validation and test procedures. Maintenance is managed through a system of anomaly and improvement forms. Computers are still evolving quickly. Therefore, after an architecture adaptation, the CYRANO3 code is now integrated in the PLEIADES platform as a PWR industrial application. The platform is an exchange space allowing sharing functionalities, models and properties. In this paper, we will give a global overview of the capabilities of CYRANO3 code to simulate the thermomechanical behavior of fuel rods, and we will focus on recent developments realized on MOX fuel. In CYRANO3 code, heterogeneous models (neutronic model, micromechanical behavior law and fission gas model) are developed for MOX fuels and integrated in order to account for differential evolutions between phases under irradiation. The methodology and these models are presented in this paper. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2004

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Fischer, Bernd↗
DOE OSTI2024

An Open-Source Parallel EMT Simulation Framework

As the integration level of inverter-based resources (IBRs) increases, ensuring the reliable operation of the bulk power systems requires the use of electromagnetic transient (EMT) simulation tools to identify and mitigate system-wide stability risks. Conducting EMT studies for large-scale, IBR-rich grids, however, is challenging due to the inherent computational bottleneck caused by the underlying high-fidelity models and required small time steps. This paper introduces ParaEMT: an open-source, generic EMT simulation framework designed to accelerate simulations by leveraging advanced parallel computational technologies, such as high-performance computers. This paper presents a comprehensive exposition of ParaEMT, covering its modeling library, simulation strategy, framework structure, operational procedures, and auxiliary features, alongside its extensible parallel computational architecture. Notably, ParaEMT is a publicly accessible and modularized framework written in Python, thereby facilitating future development and the integration of new models and algorithms. The accuracy and efficiency of ParaEMT are demonstrated by rigorous validations via multiple case studies.

electromagnetic transient simulation↗