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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 1,243 records · Page 69

All sources NASA NTRS DOE OSTI

DOE OSTI2013

Profiling an application for power consumption during execution on a compute node

Methods, apparatus, and products are disclosed for profiling an application for power consumption during execution on a compute node that include: receiving an application for execution on a compute node; identifying a hardware power consumption profile for the compute node, the hardware power consumption profile specifying power consumption for compute node hardware during performance of various processing operations; determining a power consumption profile for the application in dependence upon the application and the hardware power consumption profile for the compute node; and reporting the power consumption profile for the application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Nanocellulose in Polymer Composites and Biomedical: Research and Applications

Nanocellulose materials are nano-sized cellulose fibers or crystals that are produced by bacteria or derived from plants. These materials exhibit exceptional strength characteristics, light weight, transparency, and excellent biocompatibility. Compared to some other nanomaterials, nanocellulose is renewable and less expensive to produce. As such, a wide range of applications for nanocellulose has been envisioned. Most extensively studied areas include polymer composites and biomedical applications. Cellulose nanofibrils and nanocrystals have been used to reinforce both thermoplastic and thermoset polymers. Given the hydrophilic nature of these materials, the interfacial properties with most polymers are often poor. Various surface modification procedures have thus been adopted to improve the interaction between polymer matrix and cellulose nanofibrils or nanocrystals. In addition, the applications of nanocellulose as biomaterials have been explored including wound dressing, tissue repair, and medical implants. Nanocellulose materials for wound healing and periodontal tissue recovery have become commercially available, demonstrating the great potential of nanocellulose as a new generation of biomaterials. In this review, we highlight the applications of nanocellulose as reinforcing fillers for composites and the effect of surface modification on the mechanical properties as well as the application as biomaterials.

nanocellulose↗

DOE OSTI2012

Profiling an application for power consumption during execution on a plurality of compute nodes

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Multiphysics Application Coupling Toolkit

This particular consortium implementation of the software integration infrastructure will, in large part, refactor portions of the Rocstar multiphysics infrastructure. Development of this infrastructure originated at the University of Illinois DOE ASCI Center for Simulation of Advanced Rockets (CSAR) to support the center's massively parallel multiphysics simulation application, Rocstar, and has continued at IllinoisRocstar, a small company formed near the end of the University-based program. IllinoisRocstar is now licensing these new developments as free, open source, in hopes to help improve their own and others' access to infrastructure which can be readily utilized in developing coupled or composite software systems; with particular attention to more rapid production and utilization of multiphysics applications in the HPC environment. There are two major pieces to the consortium implementation, the Application Component Toolkit (ACT), and the Multiphysics Application Coupling Toolkit (MPACT). The current development focus is the ACT, which is (will be) the substrate for MPACT. The ACT itself is built up from the components described in the technical approach. In particular, the ACT has the following major components: 1.The Component Object Manager (COM): The COM package provides encapsulation of user applications, and their data. COM also provides the inter-component function call mechanism. 2.The System Integration Manager (SIM): The SIM package provides constructs and mechanisms for orchestrating composite systems of multiply integrated pieces.

Campbell, Michael T.↗

DOE OSTI2016

R 5 T 4 compounds - unique multifunctional intermetallics for basic research and applications

The unique properties of the rare-earth elements and their alloys have brought them from relative obscurity to high profile use in common high-tech applications. The broad technological impact of these remarkable materials may have never been known by the general public if not for the supply concerns that placed the rare-earth materials on the front page of newspapers and magazines. Neodymium and dysprosium, two essential components of Nd 2 Fe 14 B-based high-performance permanent magnets, have drawn much attention and have been deemed critical materials for many energy-related applications. Ironically, the notoriety of rare-earth elements and their alloys is the result of a global movement to reduce their use in industrial applications and, thus, ease concerns about their supply and ultimately to reduce their position in high-tech supply chains. Research into the applications of lanthanide alloys has been de-emphasized recently due to the perception that industry is moving away from the use of rare-earth elements in new products. While lanthanide supply challenges justify efforts to diversify the supply chain, a strategy to completely replace the materials overlooks the reasons rare earths became important in the first place -- their unique properties are too beneficial to ignore. Rare-earth alloys and compounds possess truly exciting potential for basic science exploration and application development such as solid-state caloric cooling. In this brief review, we touch upon several promising systems containing lanthanide elements that show important and interesting magnetism-related phenomena.

36 MATERIALS SCIENCE↗

DOE OSTI2012

Report on the ASCR Workshop on Modeling and Simulation of Exascale Systems and Applications

In the last few years, numerous studies commissioned by the Department of Energy (DOE), the Defense Advanced Research Projects Agency (DARPA), and others have examined the challenges that will have to be overcome for computational science to achieve exascale, a two order-of-magnitude increase in capability beyond what is possible today. Exponential growth in the number of devices (Moore’s Law) is expected to continue unabated, but the end of Dennard scaling, and hence the growth in performance of individual processors, has led to exponential growth in concurrency. Power consumption has also grown to the point where the cost of the electrical power for systems threatens to exceed the cost of acquiring them. Ever-shrinking devices, and the growth in their number, are expected to increase the rate of soft, or transient, errors such that applications will no longer be able to assume correct behavior of the underlying machine. Adapting to such systems will require new mathematical algorithms that minimize synchronization and data movement, and a new generation of scientific software. Rather than addressing these issues in isolation, a new process of “Co-Design” is being pursued in which application and computer scientists work toward the common goal of an exascale ecosystem of systems and applications. Modeling and simulation (ModSim) is a critical part of this process. It enables scientists and engineers to analyze future algorithms, applications, and computing systems, long before they are realized, and make the necessary design decisions such that exascale science is broadly achieved. Later, when exascale applications and systems are realized, ModSim technology will enable us to understand their behavior, debugging and optimizing them. Given the increasing importance of modeling and simulation, a workshop was organized by DOE/ASCR to assess the current state of the art and to identify research challenges that must be overcome in this field. Fifty experts, representing academia, industry, and government, participated in the workshop, and others contributed both beforehand and afterwards. This report summarizes their findings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science applications to achieve up to 4.6 times speed-up and prepare for future exascale architectures. # Goal/Relevance of Session The roofline model [1,2] is a powerful tool for analyzing the performance of applications with respect to the theoretical peak achievable on a given computer architecture. It allows one to graphically represent the performance of an application in terms of operational intensity, i.e. the ratio of flops performed and bytes moved from memory in order to guide optimization efforts. Given the scale and complexity of modern science applications, it can often be a tedious task for the user to perform the analysis on the level of functions or loops to identify where performance gains can be made. With new Intel tools, it is now possible to automate this task, as well as base the estimates of peak performance on measurements rather than vendor specifications. The goal of this session is to demonstrate how the roofline feature of Intel Advisor can be used to balance memory vs. computation related optimization efforts and effectively identify performance bottlenecks. A series of typical optimization techniques: cache blocking, structure refactoring, data alignment, and vectorization illustrated by the kernel cases will be addressed. # Description of the codes ## XGC1 The XGC1 code [3] is a magnetic fusion Particle-In-Cell code that uses an unstructured mesh for its Poisson solver that allows it to accurately resolve the edge plasma of a magnetic fusion device. After recent optimizations to its collision kernel [4], most of the computing time is spent in the electron push (pushe) kernel, where these optimization efforts have been focused. The kernel code scaled well with MPI+OpenMP but had almost no automatic compiler vectorization, in part due to indirect memory addresses and in part due to low trip counts of low-level loops that would be candidates for vectorization. Particle blocking and sorting have been implemented to increase trip counts of low-level loops and improve memory locality, and OpenMP directives have been added to vectorize compute-intensive loops that were identified by Advisor. The optimizations have improved the performance of the pushe kernel 2x on Haswell processors and 1.7x on KNL. The KNL node-for-node performance has been brought to within 30% of a NERSC Cori phase I Haswell node and we expect to bridge this gap by reducing the memory footprint of compute intensive routines to improve cache reuse. ## PICSAR is a Fortran/Python high-performance Particle-In-Cell library targeting at MIC architectures first designed to be coupled with the PIC code WARP for the simulation of laser-matter interaction and particle accelerators. PICSAR also contains a FORTRAN stand-alone kernel for performance studies and benchmarks. A MPI domain decomposition is used between NUMA domains and a tile decomposition (cache-blocking) handled by OpenMP has been added for shared-memory parallelism and better cache management. The so-called current deposition and field gathering steps that compose the PIC time loop constitute major hotspots that have been rewritten to enable more efficient vectorization. Particle communications between tiles and MPI domain has been merged and parallelized. All considered, these improvements provide speedups of 3.1 for order 1 and 4.6 for order 3 interpolation shape factors on KNL configured in SNC4 quadrant flat mode. Performance is similar between a node of cori phase 1 and KNL at order 1 and better on KNL by a factor 1.6 at order 3 with the considered test case (homogeneous thermal plasma).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Accelerators: Driving Applications for Society

We are seeking support for public outreach efforts to increase awareness with industry and the general public of Jefferson Lab’s non-mission-critical accelerator test infrastructure, pursuant to the DOE Office of Science memo dated July 28, 2014 defining the Accelerator Stewardship Test Facility Pilot Program. We plan to host an “Accelerators: Driving Applications for Society” event to increase industry and public awareness and engage students in our accelerator technologies, expertise, and capabilities and applications. Our agenda will incorporate an open plenary session highlighting Jefferson Lab’s accelerator technologies, expertise, and capabilities. Planned topical areas include Accelerators in Medicine, Accelerating Environmental Clean-up, Accelerators and Energy, Accelerating New Materials Development, and Emerging Applications of Accelerators. We will also offer a tour of our accelerator research and production facilities. Two central parts of our agenda focus on establishing and growing long-term relationships with industry leaders in currently and emerging applications of accelerators, and establishing partnerships with industry and business that help move these technologies to the commercial marketplace to address national imperatives. We are planning a panel discussion on Accelerators: Beyond Science featuring representatives from industry leaders in the above applications (We will make this a Facebook Live Event). We hope to engage these leaders in an ongoing advisory relationship to provide industry perspective on technology development. Our planned session on partnership opportunities and mechanisms will feature our processes, and build on synergy with the adjacent Tech Center Research Park, which is focused on creating “market pull” on technologies developed at Jefferson Lab as well as other federal facilities in the region. A summary of the outcome of this public outreach effort will be reported to the DOE program manager in writing within 30 days after the public outreach event.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

The TENNLab Suite of LIDAR-Based Control Applications for Recurrent, Spiking, Neuromorphic Systems

Recurrent, spiking neuromorphic systems (RSNS’s) have several desirable features compared to conventional neural networks when applied to applications that require real-time control. The TENNLab Exploratory Neuromorphic Computing Framework contains a variety of real-time control applications that use LIDAR for input, and allow a trained RSNS to make real-time decisions for navigation, surveillance and targeting. While each application is interesting on its own, the collection of applications is very useful for benchmarking RSNS’ s, evaluating training algorithms, and designing neuromorphic processing elements. In this paper, we describe the applications that compose the suite, and use them to benchmark four different RSNS’s.

Plank, James↗

DOE OSTI2020

Vertex Reordering for Real-world Graphs and Applications: An Empirical Evaluation

Vertex reordering is a way to improve locality in graph computations. Given an input (or ``natural'') order, reordering aims to compute an alternate permutation of the vertices that is aimed at maximizing a locality-based objective. Given decades of research on this topic, there are tens of graph reordering schemes, and there are also several linear arrangement ``gap'' measures for treatment as objectives. However, a comprehensive empirical analysis of the efficacy of the ordering schemes against the different gap measures, and against real-world applications is currently lacking. In this study, we present an extensive empirical evaluation of up to 11 ordering schemes, taken from different classes of approaches, on a set of 34 real-world graphs emerging from different application domains. Our study is presented in two parts: a) a thorough comparative evaluation of the different ordering schemes on their effectiveness to optimize different linear arrangement gap measures, relevant to preserving locality; and b) extensive evaluation of the impact of the ordering schemes on two real-world, parallel graph applications, namely, community detection and influence maximization. Our studies show a significant divergence among the ordering schemes (up to $40\times$ between the best and the poor) in their effectiveness to reduce the gap measures; and a wide ranging impact of the ordering schemes on various aspects including application runtime (up to $4\times$), memory and cache use, load balancing, and parallel work and efficiency. The comparative study also help reveal the nuances of a parallel environment (compared to serial) on the ordering schemes and their role in optimizing applications.

Barik, Reet↗

DOE OSTI2019

Formed-in-place Ceramic Systems for Sealing and Flow Control in Geothermal Applications

Conventional oil and gas tools are frequently unsuitable for downhole applications in geothermal wells, largely due to uncased well configurations and their extreme thermal/chemical fluid conditions. Consequently, relatively common O&G tools like bridge plugs and sand control screens are difficult or at times impossible to implement in geothermal wells. In commercial oil and gas, thermite-based tools are being developed for intervention and decommissioning applications, and gaining field experience and credibility. We are developing and testing such systems for geothermal applications, with the objective of forming ceramic sealing and flow control features in-situ. The process uses self-propagating thermite reactions, in which a metal is combined with an oxidizer to release significant amounts of energy in a controlled, non-explosive manner. These solid phase reactions can be engineered to generate ceramic products with specific physical and flow characteristics. We are developing and testing formulations and wireline deployment tools which yield low to high permeability as needed, and preferentially expand to fill boreholes in both large diameter and slimhole wells. Near term applications are bridge plugs for P&A operations, screens for sand control and borehole stabilization, and lost circulation control during drilling. Laboratory tests have demonstrated the ability to form these products under high temperature and pressure conditions. Field tests are in planning to demonstrate the full-scale performance of these tools. This paper will present the status and results of this demonstration project, in its first year of advanced development for the DOE geothermal technologies program. New developments utilizing thermite tools in the HP/HT oil and gas domain will also be highlighted, particularly those which may have utility in geothermal applications.

02 PETROLEUM↗

DOE OSTI2012

Report on the ASCR Workshop on Modeling and Simulation of Exascale Systems and Applications

In the last few years, numerous studies commissioned by the Department of Energy (DOE), the Defense Advanced Research Projects Agency (DARPA), and others have examined the challenges that will have to be overcome for computational science to achieve exascale, a two order-of-magnitude increase in capability beyond what is possible today. Exponential growth in the number of devices (Moore's Law) is expected to continue unabated, but the end of Dennard scaling, and hence the growth in performance of individual processors, has led to exponential growth in concurrency. Power consumption has also grown to the point where the cost of the electrical power for systems threatens to exceed the cost of acquiring them. Ever-shrinking devices, and the growth in their number, are expected to increase the rate of soft, or transient, errors such that applications will no longer be able to assume correct behavior of the underlying machine. Adapting to such systems will require new mathematical algorithms that minimize synchronization and data movement, and a new generation of scientific software. Rather than addressing these issues in isolation, a new process of "Co-Design" is being pursued in which application and computer scientists work toward the common goal of an exascale ecosystem of systems and applications. Modeling and simulation (ModSim) is a critical part of this process. It enables scientists and engineers to analyze future algorithms, applications, and computing systems, long before they are realized, and make the necessary design decisions such that exascale science is broadly achieved. Later, when exascale applications and systems are realized, ModSim technology will enable us to understand their behavior, debugging and optimizing them. Given the increasing importance of modeling and simulation, a workshop was organized by DOE/ASCR to assess the current state of the art and to identify research challenges that must be overcome in this field. Fifty experts, representing academia, industry, and government, participated in the workshop, and others contributed both beforehand and afterwards. This report summarizes their findings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Is Knowledge About Running Applications Helping Improve Runtime Prediction of HPC Jobs?

High-performance computing systems rely upon scheduling algorithms to achieve high utilization. These schedulers rely upon user estimates of job resource requirements, such as runtime, to determine optimal scheduling of incoming jobs. These user estimates, however, are prone to error. To mitigate this error, significant research has been directed at providing better estimates of job runtime, usually employing machine learning techniques. These techniques are dependent upon the input features selected. Among the possible features is the primary application used by the job. In a survey of more than 20 papers directed at improving runtime prediction, only four included primary application as an input feature. We focus this investigation specifically on the value of adding primary application as an input feature, and find that it does improve model performance, especially for jobs with longer runtimes, though this improvement varies based on the application used. We recommend further research to determine the cause of this variability as well as an optimal strategy for employing a mixture of models both including and not including primary application as a feature.

feature selection↗

DOE OSTI2015

D and D decision model and mobile application for selection of fixative, strippable coating, and decontamination gel products - 15696

Deactivation and decommissioning (D and D) is the process of taking an active/excess/abandoned facility to a final disposition end state. D and D presents unique hazards that must be addressed from a safety, programmatic, environmental, and technological standpoint. This definition is especially applicable to Savannah River Site's 235-F facility. The facility was constructed in the 1950's as part of the weapons complex materials production and fabrication. The most significant quantities of residual contamination remaining in 235-F building is in the form of Plutonium-238. A Decision Model was created using MatLab to work hand-in-hand with a product list containing commercially available D and D products. This model was created to further enhance and accelerate the decontamination process. It is envisioned that D and D engineers will be able to use this Decision Model in the field via a mobile device. It allows the user to select four inputs to match their situation. The model searches the database and returns the products that fit the criteria selected by the user. This Decision Model will be made available in a web-based application and as a mobile application to ensure end users can access it when needed. The MatLab code recognizes what position in the text box is selected and then this input is converted to the corresponding string. The string is then compared with the information in the product list in the specified column in order to reduce processing time. Then the products that contain the string inputted are displayed on the table and are separated by category. The web-based version of the model will receive three specified criteria and sub-criteria from the user and update the table with products that fit each criteria. A web-based version of this Decision Model is under way and will be set up on the D and D KM-IT platform. There will be two versions of this mobile application: for devices with internet connection and for those that do not have internet connection. This will ensure end users have access to the Decision application at any time or place during the D and D process. A mobile version of the model will also be developed in the near future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Quantification of calculation accuracy for code systems in burn-up credit applications by recalculations of experimental data - 14480

For application in criticality safety, numerical code systems require profound validation against experimental data. In terms of burn-up credit, this refers to the inventory determination as well as the subsequent criticality calculation. Within this framework, a dedicated, conservative estimation of uncertainties, bias and bias uncertainties for the resulting calculated multiplication factor k{sub eff} is indispensable. However, measures to reduce excess conservatism may become desirable, depending on the application case. For this reason GRS implemented a methodology to validate a calculation code system for criticality safety analyses for systems with irradiated nuclear fuel. The work at hand demonstrates this methodology by means of the GRS home-built inventory determination system KENOREST and ORNL's well-known SCALE 6 CSASS criticality safety calculation sequence. A number of 40 radiochemical analysis samples taken from SFCOMPO and elsewhere have been calculated to derive isotopic correction factors in different ways, depending on the required level of conservatism and the calculational efforts to be carried out. This includes bounding methods as well as different Monte Carlo sampling approaches. Furthermore, from the ICSBEP a number of 515 critical benchmark experiment configurations comprising water moderated low enriched UO{sub 2} fuel rods and water moderated mixed oxide (MOX) fuel rods have been selected and evaluated. Important absorber and structure materials are also covered. Various trending and sensitivity and uncertainty analysis methods have been applied, again to derive conservative estimates on the various contributions to k{sub eff} uncertainties. The overall methodology is applicable to low enriched, water moderated PWR uranium dioxide fuels in a burn-up range of about 10 to 60 GWd/tHM, and validates the reactivity contributions of the major uranium and plutonium isotopes. The methodology itself has no limitation which requires the exclusion of further isotopes as e.g. fission products. However, its application is constrained by the experimental database being publicly available. After the potential provision of an extended database in the future, the range of applicability can easily be extended to more nuclides. In addition, it is not limited to the code systems being used here but can also be applied using different numerical tools. For a generic PWR spent fuel pool rack and different enrichment and burn-up combinations, the impact of the current level of validation on k{sub eff} is demonstrated and quantified. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2014

Recycled Water Reuse Permit Renewal Application for the Central Facilities Area Sewage Treatment Plant

This renewal application for a Recycled Water Reuse Permit is being submitted in accordance with the Idaho Administrative Procedures Act 58.01.17 “Recycled Water Rules” and the Municipal Wastewater Reuse Permit LA-000141-03 for continuing the operation of the Central Facilities Area Sewage Treatment Plant located at the Idaho National Laboratory. The permit expires March 16, 2015. The permit requires a renewal application to be submitted six months prior to the expiration date of the existing permit. For the Central Facilities Area Sewage Treatment Plant, the renewal application must be submitted by September 16, 2014. The information in this application is consistent with the Idaho Department of Environmental Quality’s Guidance for Reclamation and Reuse of Municipal and Industrial Wastewater and discussions with Idaho Department of Environmental Quality personnel.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

Machine learning (ML) and artificial intelligence (AI) algorithms offer valuable tools for the analysis and interpretation of large datasets. These tools have the capability to uncover insights that may not be readily apparent within these datasets. In recent years, the integration of ML and AI has become increasingly prevalent in various applications within the power system domain. One of the earliest instances of machine learning in power systems can be traced back to demand forecasting, where artificial neural networks were employed for short-term load forecasting. In contemporary power systems, an abundance of high-resolution geospatial and temporal data is generated at various time intervals, ranging from sub-seconds (Phasor Measurement Units or PMUs) to seconds (Supervisory Control and Data Acquisition or SCADA), minutes (Process Information or PI), and extending to days, months, and years. These datasets contain valuable information concerning system reliability and performance. This information holds the potential to offer critical insights into system operations, as well as solutions for predicting and mitigating contingencies to prevent cascading outages. Despite the immense power of machine learning tools, system operators, planners, and utilities often exhibit hesitancy in fully embracing AI-enabled system operations and planning. This cautious approach persists, even as numerous diverse applications of machine learning continue to emerge in the realm of power systems. In this chapter, our focus will delve deep into ML and AI applications tailored for power systems. These applications aim to furnish system operators with enhanced situational awareness and augment their decision-making capabilities, especially during challenging operating conditions. Specific areas of interest encompass root cause analyses of electricity market datasets and the strategic selection of representative samples from vast power system databases for training ML/AI models. Finally, the chapter will conclude with a short discussion on the future of ML/AI in power systems and possible directions that the industry is moving towards.

power system applications, machine learning (ML), ↗

DOE OSTI2024

FREDA: A Web Application for the Processing, Analysis, and Visualization of Fourier‐Transform Mass Spectrometry Data

The high-resolution measurement capability of Fourier-transform mass spectrometry (FT-MS) has made it a necessity for exploring the molecular composition of complex organic mixtures, like soil, plant, aquatic, and petroleum samples. This demand has driven a need for informatics tools to explore and analyze FT-MS data in a robust and reproducible manner. FREDA is an interactive web application developed to enable spectrometrists to format, process, and explore their FT-MS data without the need for statistical programming expertise. FREDA was built to explore outputs from a molecular identification tool, like CoreMS, and provide a suite of methods to filter data, compute chemical properties of peaks, statistically compare samples and groups of samples, conduct exploratory data analysis, and download the results with a report detailing all steps conducted. To demonstrate the utility of FREDA, an example analysis was conducted using FT-MS data from a soil microbiology study of samples collected in two different soil depths at the Sphagnum bog forest north of Grand Rapids, Minnesota. Differences between the two depths are observed using Kendrick, Gibbs free energy, and van Krevelen plots. G-tests are used to quantify a significant difference between the groups. All analyses and plotting are conducted using only the FREDA application. FREDA is an open-source and readily available web application that allows users to explore and make statistically valid conclusions about their FT-MS data. The application is available online (https://map.emsl.pnnl.gov/app/freda) with a tutorial web series (https://youtu.be/k5HLE2kNSBY?si=yB6sGoyvzxrFf5MP) and freely accessible code on Github (https://github.com/EMSL-Computing/FREDA).

47 OTHER INSTRUMENTATION↗