Search NASA⌕ Search

SEARCH · Search NASA

Results for “software estimation”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

SIDSIM (Sub-Interval Distribution-function in Simulation) [SWR-17-22]

Time-series simulation is a technique used to estimate the energy delivery of a power generation system with output that changes under changing conditions. Such variable resources include photovoltaic energy systems that experience different levels of sunlight or wind farms with changing wind patterns. As distributed generation from these variable resources continues to flourish, having improved software tools to accurately measure, model, and estimate phenomena of interest to grid integration, in addition to energy output, will be crucial for safeguarding smooth integration and operation of these energy systems. Currently, time-series simulations assume conditions and power output are constant over the duration of a time-step (steady-state assumption). NREL researchers improve the accuracy with a new simulation software called SIDSIM (Sub-Interval Distribution Simulation) that replaces this steady value (solar or wind resource) with a distribution function that has a maximum value, a minimum value, and a shape to the curve within each time-step. The distribution function used for modeling varying values in the SIDSIM software is a novel equation and presents advantageous new benefits over the conventional methods. The first advantage comes in the ability to determine maximum instantaneous power within a time-step. This enables better protection of a system from overcurrent issues and it also allows for better forecasting and reservation of transmission capacity; such capabilities are essential for energy system integration. Second, a distribution function helps to determine the amount of energy loss due to “clipping” in cases where the photovoltaic direct current (DC) system capacity exceeds the inverter capacity, the AC interconnect capacity, or any other limiting component or threshold value. It improves estimates of battery throughput by allowing both charge and discharge of a battery within the duration of a time-step. Third, it provides a more refined estimate of utility-bill impacts by considering the delivered power may be higher than the site load or lower than the regular average power estimates that are made using a quasi-steady-state assumption. SEE ALSO OSTI ID 1,361,018

Walker, Andy↗
DOE OSTI2015

IDC Reengineering Phase 2 Project Scope

The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) operates the International Data Centre (IDC) to support treaty verification activities by Member States. The IDC collects, stores, processes, and distributes data from seismic, hydroacoustic, infrasound, and radionuclide stations. A significant component of the IDC is the seismic, hydroacoustic, and infrasound (SHI) processing system. The IDC has recognized the need to reengineer the SHI processing system and has defined a three-phase reengineering effort. IDC Reengineering Phase 1 (RP1) started in 2011 with the goal to significantly modernize SHI automatic and interactive data processing software, focusing on enhancements to individual components of the system. Reengineering Phase 2 (RP2), started in 2014, addresses the task of specifying a unified architecture for all SHI software, across processing stages, to pave the way for further software development and sustainment in the future. A key objective of RP2 is an architecture sufficient to provide a basis for a cost estimate for the development or enhancement of the software components and subsystems. This report provides a brief description of the scope of the IDC Reengineering Phase 2 project. It describes the goals and objectives of reengineering, the system definition, and the technical scope of the system.This report expands upon the “Scope for IDC Reengineering Phase 2”, July 2014, ECS-DIS-WGB-43-PTS-MATERIAL-12-ADD-1, produced by the IDC.

58 GEOSCIENCES↗
DOE OSTI2024

BlendPATH (Blending Pipeline Analysis Tool for Hydrogen) [SWR-24-10]

BlendPATH provides case-by-case techno-economic analysis for potential projects where hydrogen is blended into a natural gas transmission pipeline. BlendPATH estimates 1) the transmission pipeline modifications and operating conditions necessary to blend hydrogen to a user specified volume faction of hydrogen in pipeline gas and 2) the incremental capital and operating expenses to prepare said transmission pipeline for hydrogen blending. BlendPATH is developed in Python and requires SAInt, a underlying commercial natural gas pipeline network modeling software, to run. Pipeline modification and operation condition estimation is guided by ASME B31.12. The intent of this software is to target application for projects in the initial project assessment stage and provide the user with the capability of assess promising opportunities before the use proceeds with further detailed pipeline evaluation based on a probable economic outcome.

Kee, Jamie↗
DOE OSTI2022

The EBLM project – IX. Five fully convective M-dwarfs, precisely measured with CHEOPS and TESS light curves

ABSTRACT Eclipsing binaries are important benchmark objects to test and calibrate stellar structure and evolution models. This is especially true for binaries with a fully convective M-dwarf component for which direct measurements of these stars’ masses and radii are difficult using other techniques. Within the potential of M-dwarfs to be exoplanet host stars, the accuracy of theoretical predictions of their radius and effective temperature as a function of their mass is an active topic of discussion. Not only the parameters of transiting exoplanets but also the success of future atmospheric characterization relies on accurate theoretical predictions. We present the analysis of five eclipsing binaries with low-mass stellar companions out of a subsample of 23, for which we obtained ultra-high-precision light curves using the CHEOPS satellite. The observation of their primary and secondary eclipses are combined with spectroscopic measurements to precisely model the primary parameters and derive the M-dwarfs mass, radius, surface gravity, and effective temperature estimates using the PYCHEOPS data analysis software. Combining these results to the same set of parameters derived from TESS light curves, we find very good agreement (better than 1 per cent for radius and better than 0.2 per cent for surface gravity). We also analyse the importance of precise orbits from radial velocity measurements and find them to be crucial to derive M-dwarf radii in a regime below 5 per cent accuracy. These results add five valuable data points to the mass–radius diagram of fully convective M-dwarfs.

Sebastian, D. (ORCID:0000000222149258)↗
DOE OSTI2019

TestSNAP

TestSNAP is a stand-alone prototype of the SNAP force kernel used in the LAMMPS molecular dynamics code. It contains synthetic input data (neighbor atom positions) and reference output data (forces on atoms) for several different SNAP models. The prototype performs the force calculation repeatedly, checking the results against the reference data. At the end it reports the grind time [msec/atomstep] and RMS force error [eV/A]. This allows performance experts to quickly test new hardware and software strategies, obtain a realistic performance estimate and verify that the computation was performed correctly. SAND2019-12243 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Thompson, Aidan↗
DOE OSTI2013

Autonomous Intelligent Assembly Systems LDRD 105746 (Final Report)

This report documents a three-year to develop technology that enables mobile robots to perform autonomous assembly tasks in unstructured outdoor environments. This is a multi-tier problem that requires an integration of a large number of different software technologies including: command and control, estimation and localization, distributed communications, object recognition, pose estimation, real-time scanning, and scene interpretation. Although ultimately unsuccessful in achieving a target brick stacking task autonomously, numerous important component technologies were nevertheless developed. Such technologies include: a patent-pending polygon snake algorithm for robust feature tracking, a color grid algorithm for uniquely identification and calibration, a command and control framework for abstracting robot commands, a scanning capability that utilizes a compact robot portable scanner, and more. This report describes this project and these developed technologies.

Anderson, Robert J.↗
DOE OSTI2022

Analysis of FRAM Measurements to Establish Methodology Uncertainty

Qualification measurements were performed at Oak Ridge National Laboratory (ORNL) on a variety of measurement standards. These measurements will be used to qualify the Fixed-Energy, Response Function Analysis with Multiple Efficiency (FRAM) code with a high purity germanium (HPGe) detector for use at ORNL. Measured items include uranium isotopic standards, U 3 O 8 line sources, and a uranium tetrafluoride source. The 235 U enrichment was estimated using the FRAM isotopic analysis software for each source and compared with the declared isotopic values.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

A Gamma Assay System for Characterizing Excavated Soil with High {sup 137}Cs and {sup 90}Sr Contamination - 19460

We report on the recent development of a remote gamma-assay system for the measurement and characterization of high-activity soil excavated as part of an ongoing remediation project. The soil below a hot cell in our customer's facility has been contaminated with high concentrations of radionuclides {sup 137}Cs and {sup 90}Sr over the past several decades. The contaminated soil is to be remotely excavated from beneath the hot cell floor, to a depth of several feet, and placed in steel-walled waste bins for assay and disposition. The project requires measuring the {sup 137}Cs activity to a minimum detectable concentration (MDC) of 1 micro curie per gram. The high dose-rate of the material and the expectation of high Bremsstrahlung background, due to an unknown ratio of {sup 90}Sr admixture with the {sup 137}Cs, present unique measurement challenges. A novel assay system was designed to make measurements through a small access port in a 4-foot thick concrete wall isolating operators from the high-dose excavation area. Waste bins filled with soil are placed by a remotely operated crane onto an automated turntable, and initial dose measurements are taken for all bins. When excavation has proceeded to the point that dose rates below 20 Rad/hr on contact are reached, gamma spectroscopy will be used to characterize the {sup 137}Cs content. Gamma assay is performed with a 1 cm{sup 3} CZT detector in a collimated tungsten shield, which is extended through the access port toward the side of the bin by means of a seven foot long aluminum pipe. Each of the four sides of the bin is assayed in a discrete measurement, and the individual segments and summed result are reported. Canberra's NDA2000 software is used to collect and analyze the spectroscopic data and to control the turntable movement during the assay. The system is expected to meet the required MDC limits within a forty minute assay time under the most adverse conditions anticipated, with total measurement uncertainty of less than 25%. We describe in this paper the design and construction of the assay system, its calibration using the ISOCS software, and the evaluation of performance estimates. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Analyzing Hardware and Software Common Cause Failures in Digital Instrumentation and Control Systems using Dual Error Propagation Method

This paper develops a methodology for quantifying software common cause failures (CCFs) in digital instrumentation and control (I&C) systems of nuclear power plants. To support the transition of analog I&C systems to digital in nuclear power plants, probabilistic risk assessment (PRA) techniques are used. The hardware components of the I&C systems have reliability databases that can be used in the PRA studies. However, the failure data for redundant software components of the systems is sparse. Failure of components constitutes a CCF, wherein two or more components or systems fail due to a single shared cause and coupling mechanism. This paper proposes a quantification approach that can simultaneously model hardware and software components, incorporate the CCFs of software systems in the models, and bridge the gap between the failure quantification of models and the development of CCF parametric databases. We demonstrate the dual error propagation method (DEPM) by developing I&C systems failure models for a representative digital reactor trip system. The DEPM models are built to simulate the control and data flows within the systems and can accommodate failure states. By expanding DEPM to software CCFs, we generated alpha factor parameter estimates for each of the modeled error propagation mechanisms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

On a stochastic approach to a code performance estimation

The main goal of an efficient profiling of software is to minimize the runtime overhead under certain constraints and requirements. The traces built by a profiler during the work, affect the performance of the system itself. One of important aspect of an overhead arises from the randomness of variability in the context in which the application is embedded, e.g., due to possible cache misses, etc. Such uncertainty needs to be taken into account in the design phase. In order to overcome these difficulties we propose to investigate this issue through the analysis of the probability distribution of the difference between profiler’s times for the same code. The approximating model is based on the finite normal mixtures within the framework of the method of moving separation of mixtures. We demonstrate some results for the MATLAB profiler using plotting of 3D surfaces by the function surf. The idea can be used for an estimating of a program efficiency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Deformation analysis of Aceh April 11{sup th} 2012 earthquake using GPS observation data

This research tries to estimate the co-seismic deformation of intraplate earthquake occurred off northern Sumatra coast which is about 100-200 km southwest of Sumatrasubduction zone. The earthquake mechanism was strike-slip with magnitude 8.6 and triggering aftershock with magnitude 8.2 two hours later. We estimated the co-seismic deformation by using the GPS (Global Positioning System) continuous data along western Sumatra coast. The GPS observation derived from Sumatran GPS Array (SuGAr) and Geospatial Information Agency (BIG). For data processing we used GPS Analyze at Massachusetts Institute of Technology (GAMIT) software and Global Kalman Filter (GLOBK) to estimate the co-seismic deformation. From the GPS daily solution, the result shows that the earthquake caused displacement for the GPS stations in Sumatra. GPS stations in northern Sumatra showed the displacement to the northeast with the average displacement was 15 cm. The biggest displacement was found at station BSIM which is located at Simeuleu Island off north west Sumatra coast. GPS station in middle part of Sumatra, the displacement was northwest. The earthquake also caused subsidence for stations in northern Sumatra, but from the time series there was not sign of subsidence was found at middle part of Sumatra. In addition, the effect of the earthquake was worldwide and affected the other GPS Stations around Hindia oceanic.

58 GEOSCIENCES↗
DOE OSTI2013

Metrological characterization of X-ray diffraction methods at different acquisition geometries for determination of crystallite size in nano-scale materials

Crystallite size values were determined by X-ray diffraction methods for 183 powder samples. The tested size range was from a few to about several hundred nanometers. Crystallite size was calculated with direct use of the Scherrer equation, the Williamson–Hall method and the Rietveld procedure via the application of a series of commercial and free software. The results were statistically treated to estimate the significance of the difference in size resulting from these methods. We also estimated effect of acquisition conditions (Bragg–Brentano, parallel-beam geometry, step size, counting time) and data processing on the calculated crystallite size values. On the basis of the obtained results it is possible to conclude that direct use of the Scherrer equation, Williamson–Hall method and the Rietveld refinement employed by a series of software (EVA, PCW and TOPAS respectively) yield very close results for crystallite sizes less than 60 nm for parallel beam geometry and less than 100 nm for Bragg–Brentano geometry. However, we found that despite the fact that the differences between the crystallite sizes, which were calculated by various methods, are small by absolute values, they are statistically significant in some cases. The values of crystallite size determined from XRD were compared with those obtained by imaging in a transmission (TEM) and scanning electron microscopes (SEM). It was found that there was a good correlation in size only for crystallites smaller than 50 – 60 nm. Highlights: • The crystallite sizes for 183 nanopowders were calculated using different XRD methods • Obtained results were subject to statistical treatment • Results obtained with Bragg-Brentano and parallel beam geometries were compared • Influence of conditions of XRD pattern acquisition on results was estimated • Calculated by XRD crystallite sizes were compared with same obtained by TEM and SEM.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Comparison of internal dose estimates obtained using organ-level, voxel S value, and Monte Carlo techniques

Purpose: The authors’ objective was to compare internal dose estimates obtained using the Organ Level Dose Assessment with Exponential Modeling (OLINDA/EXM) software, the voxel S value technique, and Monte Carlo simulation. Monte Carlo dose estimates were used as the reference standard to assess the impact of patient-specific anatomy on the final dose estimate. Methods: Six patients injected with{sup 99m}Tc-hydrazinonicotinamide-Tyr{sup 3}-octreotide were included in this study. A hybrid planar/SPECT imaging protocol was used to estimate {sup 99m}Tc time-integrated activity coefficients (TIACs) for kidneys, liver, spleen, and tumors. Additionally, TIACs were predicted for {sup 131}I, {sup 177}Lu, and {sup 90}Y assuming the same biological half-lives as the {sup 99m}Tc labeled tracer. The TIACs were used as input for OLINDA/EXM for organ-level dose calculation and voxel level dosimetry was performed using the voxel S value method and Monte Carlo simulation. Dose estimates for {sup 99m}Tc, {sup 131}I, {sup 177}Lu, and {sup 90}Y distributions were evaluated by comparing (i) organ-level S values corresponding to each method, (ii) total tumor and organ doses, (iii) differences in right and left kidney doses, and (iv) voxelized dose distributions calculated by Monte Carlo and the voxel S value technique. Results: The S values for all investigated radionuclides used by OLINDA/EXM and the corresponding patient-specific S values calculated by Monte Carlo agreed within 2.3% on average for self-irradiation, and differed by as much as 105% for cross-organ irradiation. Total organ doses calculated by OLINDA/EXM and the voxel S value technique agreed with Monte Carlo results within approximately ±7%. Differences between right and left kidney doses determined by Monte Carlo were as high as 73%. Comparison of the Monte Carlo and voxel S value dose distributions showed that each method produced similar dose volume histograms with a minimum dose covering 90% of the volume (D90) agreeing within ±3%, on average. Conclusions: Several aspects of OLINDA/EXM dose calculation were compared with patient-specific dose estimates obtained using Monte Carlo. Differences in patient anatomy led to large differences in cross-organ doses. However, total organ doses were still in good agreement since most of the deposited dose is due to self-irradiation. Comparison of voxelized doses calculated by Monte Carlo and the voxel S value technique showed that the 3D dose distributions produced by the respective methods are nearly identical.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Machine Learning Based System for Automated Estimation of Crystal Unit Cell Parameters from X-ray Diffraction Powder Patterns (MLCell) v0.1

This software uses machine learning models to perform inference on X-ray diffraction powder patterns, output from a diffractometer, to estimate all 6 unit cell parameters of crystalline lattices. Novel aspects of this software originated from the incorporation of concepts from crystallography to an ML-based approach; The resulting method achieves new performance capabilities without significant loss of accuracy and with less computationally intensive models.

Oklejas, Vanessa↗
DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify if the software is reliable (or unreliable) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Software Quality Metrics for Geant4: An Initial Assessment - Paper 122

In the context of critical applications, such as shielding and radiation protection, ensuring the quality of simulation software they depend on is of utmost importance. The assessment of simulation software quality is crucial both to determine its adoption in experimental applications and to guarantee reproducibility of outcome over time. Geant4 is a simulation system used in a wide range of experimental applications, some of which, such as radiation protection and biomedical studies, may involve critical use cases and would especially profit from an objective assessment of the software quality. In this study, we present the first results from an ongoing analysis of Geant4 code based on established software metrics from the perspective of software engineering. The analysis evaluates the current status of the code to quantify its characteristics with respect to documented quality standards; further appraisals concern evolutions over a series of release distributions. The quantitative assessment of the software is initially focused on a subset of Geant4 packages, which play a key role in scientific applications and are representative of different software development processes. We describe the chosen software metrics that map the entities of a software system to numeric values through mathematical definitions, quantifying software attributes ranging from functionality to maintainability. To measure such metrics, we exploited a set of software metrics tools, i.e. programs that implement a set of software metrics definitions. They allow software engineers to assess a software system by extracting the required attributes from the software and providing the corresponding metric values. To correlate software metrics values in a well-defined way, we used software quality standard models, such as the ISO/IEC 9126 standard, which aggregate numerical values to aid quality analysis and assessment. With this work we aim to create a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. Furthermore, we intend to highlight what metrics are most effective at evaluating radiation transport software quality. We are confident that the result will provide constructive guidance both to improve key software tools, such as Geant4, and to estimate their contribution in risk analysis concerning sensitive applications. The remainder of this paper is structured as follows. We first discuss the approach adopted to fulfil our assessment. Then, we present the setup of our experiments and the way we collected data. We provide an initial interpretation of a subset of data resulting from measurements made on the selected Geant4 packages. As the analysis is still ongoing at the time of submitting this abstract, some results will be documented in the final paper and in the conference presentation. With this work we aim to create a proper Geant4 data set for evaluating its software characteristics and identifying both strengths and weaknesses. In this initial study, we considered the geometry and processes packages, which play a major role in most simulation applications. The data analysis is in progress at the time of writing; its complexity is related to the differences among software metrics tools, to the large amount of data to be evaluated and to the pioneering character of this project. We are confident that the results will provide valuable indications for the Geant4 user community and constructive guidance to improve key Geant4 packages. Other Monte Carlo codes could profit from the methodology developed in this pilot project for similar assessments of their software quality. At the end of this study, we intend to create a baseline for evaluating correlations between software quality embedded in the Geant4 development process and simulation observables produced by Geant4-based applications. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Quantification and evaluation of strain reduction from small-bubble gas injection in Spallation Neutron Source target vessels

Small-bubble gas injection has been routinely utilized in the operation of Spallation Neutron Source (SNS) mercury targets since 2017 to mitigate cavitation-induced erosion damage to target vessels. Strain measurements of target vessels collected in-situ during initial operation with gas injection were used to study the gas injection effect on the structural response of targets to proton pulses. A significant strain reduction owing to gas injection was found by comparing the strain measurement data during operation with and without gas injection. The research presented here focuses on quantifying strain reductions in SNS targets and evaluating the effect of small-bubble gas injection by comparing different bubbler types and target designs. The strain measurement results show the gas injection significantly reduced strain in SNS target vessels; strain values decreased by 30% to 80% for targets operating with gas injection. Stress and strain responses of SNS targets were simulated to numerically evaluate the gas injection effect. Based on the predicted stresses with and without gas injection, the fatigue lifetimes of SNS jet-flow design target were estimated using fe-safe fatigue analysis software. The simulations show these reductions should improve the fatigue life of target vessels and allow SNS targets to meet their fatigue design goal.

Fatigue life estimation↗