Results for “Reporting” — Page 31

NASA NTRS2003

Columbia Accident Investigation Board Report. Volume Two

Volume II of the Report contains appendices that were cited in Volume I. The Columbia Accident Investigation Board produced many of these appendices as working papers during the investigation into the February 1, 2003 destruction of the Space Shuttle Columbia. Other appendices were produced by other organizations (mainly NASA) in support of the Board investigation. In the case of documents that have been published by others, they are included here in the interest of establishing a complete record, but often at less than full page size. Contents include: CAIB Technical Documents Cited in the Report: Reader's Guide to Volume II; Appendix D. a Supplement to the Report; Appendix D.b Corrections to Volume I of the Report; Appendix D.1 STS-107 Training Investigation; Appendix D.2 Payload Operations Checklist 3; Appendix D.3 Fault Tree Closure Summary; Appendix D.4 Fault Tree Elements - Not Closed; Appendix D.5 Space Weather Conditions; Appendix D.6 Payload and Payload Integration; Appendix D.7 Working Scenario; Appendix D.8 Debris Transport Analysis; Appendix D.9 Data Review and Timeline Reconstruction Report; Appendix D.10 Debris Recovery; Appendix D.11 STS-107 Columbia Reconstruction Report; Appendix D.12 Impact Modeling; Appendix D.13 STS-107 In-Flight Options Assessment; Appendix D.14 Orbiter Major Modification (OMM) Review; Appendix D.15 Maintenance, Material, and Management Inputs; Appendix D.16 Public Safety Analysis; Appendix D.17 MER Manager's Tiger Team Checklist; Appendix D.18 Past Reports Review; Appendix D.19 Qualification and Interpretation of Sensor Data from STS-107; Appendix D.20 Bolt Catcher Debris Analysis.

CAIB (COLUMBIA ACCIDENT INVESTIGATION BOARD)↗

NASA NTRS2004

TOPEX Radar Altimeter Engineering Assessment Report Update: Side B Turn-On to January 1, 2004

This is the eleventh in a series of TOPEX Radar Engineering Assessment Reports, The initial TOPEX Radar Altimeter Engineering Assessment Report, in February 1994, presented performance results for the NASA Radar Altimeter on the TOPEX/POSEIDON spacecraft, from the time of its launch in August 1992 to February 1994. Since the time of that initial report and prior to this report, there have been nine interim supplemental Engineering Assessment Reports, issued in March 1995, May 1996, March 1997, June 1998, August 1999, September 2000, June 2001, March 2002 and again in May 2003.The sixth supplement in September 2000 was the first assessment report that addressed Side B performance, and presented the altimeter performance from the turn-on of Side B until the end of calendar year 1999. This report extends the performance assessment of Side B to the end of calendar year 2003 and includes the performance assessment of Jason-1, the TOPEX follow-on mission, launched on December 7, 2001.

Hancock, David W., III↗

NASA NTRS2010

2010 NASA Range Safety Annual Report

this report provides a NASA Range Safety overview for current and potential range users. This report contains articles which cover a variety of subject areas, summaries of various NASA Range Safety Program activities conducted during the past year, links to past reports, and information on several projects that may have a profound impact on the way business will be done in the future. Specific topics discussed in the 2010 NASA Range Safety Annual Report include a program overview and 2010 highlights; Range Safety Training; Range Safety Policy revision; Independent Assessments; Support to Program Operations at all ranges conducting NASA launch/flight operations; a continuing overview of emerging range safety-related technologies; and status reports from all of the NASA Centers that have Range Safety responsibilities. Every effort has been made to include the most current information available. We recommend this report be used only for guidance and that the validity and accuracy of all articles be verified for updates. Once again, the web-based format was used to present the annual report.

Dumont, Alan G.↗

NASA NTRS2008

2008 NASA Range Safety Annual Report

Welcome to the 2008 edition of the NASA Range Safety Annual Report. Funded by NASA Headquarters, this report provides a NASA Range Safety overview for current and potential range users. This year, along with full length articles concerning various subject areas, we have provided updates to standard subjects with links back to the 2007 original article. Additionally, we present summaries from the various NASA Range Safety Program activities that took place throughout the year, as well as information on several special projects that may have a profound impact on the way we will do business in the future. The sections include a program overview and 2008 highlights of Range Safety Training; Range Safety Policy; Independent Assessments and Common Risk Analysis Tools Development; Support to Program Operations at all ranges conducting NASA launch operations; a continuing overview of emerging Range Safety-related technologies; Special Interests Items that include recent changes in the ELV Payload Safety Program and the VAS explosive siting study; and status reports from all of the NASA Centers that have Range Safety responsibilities. As is the case each year, contributors to this report are too numerous to mention, but we thank individuals from the NASA Centers, the Department of Defense, and civilian organizations for their contributions. We have made a great effort to include the most current information available. We recommend that this report be used only for guidance and that the validity and accuracy of all articles be verified for updates. This is the third year we have utilized this web-based format for the annual report. We continually receive positive feedback on the web-based edition, and we hope you enjoy this year's product as well. It has been a very busy and productive year on many fronts as you will note as you review this report. Thank you to everyone who contributed to make this year a successful one, and I look forward to working with all of you in the years to come.

Lamoreaux, Richard W.↗

NASA NTRS2011

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 900,000 reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 5,500 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides de-identified report information through the online ASRS Database at http://asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation \vill discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda↗

NASA NTRS2013

International VLBI Service for Geodesy and Astrometry 2012 Annual Report

This volume of reports is the 2012 Annual Report of the International VLBI Service for Geodesy and Astrometry (IVS). The individual reports were contributed by VLBI groups in the international geodetic and astrometric community who constitute the permanent components of IVS. The IVS 2012 Annual Report documents the work of the IVS components for the calendar year 2012, our fourteenth year of existence. The reports describe changes, activities, and progress ofthe IVS. Many thanks to all IVS components who contributed to this Annual Report. With the exception of the first section and parts of the last section (described below), the contents of this Annual Report also appear on the IVS Web site athttp:ivscc.gsfc.nasa.gov/publications/ar2012

VLBI↗

NASA NTRS2014

International VLBI Service for Geodesy and Astrometry 2013 Annual Report

This volume of reports is the 2013 Annual Report of the International VLBI Service for Geodesy and Astrometry (IVS). The individual reports were contributed by VLBI groups in the international geodetic and astrometric community who constitute the permanent components of IVS. The IVS 2013 Annual Report documents the work of the IVS components for the calendar year 2013, our fifteenth year of existence. The reports describe changes, activities, and progress of the IVS. Many thanks to all IVS components who contributed to this Annual Report. With the exception of the first section and the last section, the contents of this Annual Report also appear on the IVS Web site at http://ivscc.gsfc.nasa.gov/publications/ar2013.

VLBI↗

NASA NTRS2017

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 million reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda J.↗

NASA NTRS2016

NASA Aviation Safety Reporting System (ASRS)

The NASA Aviation Safety Reporting System (ASRS) collects, analyzes, and distributes de-identified safety information provided through confidentially submitted reports from frontline aviation personnel. Since its inception in 1976, the ASRS has collected over 1.4 M reports and has never breached the identity of the people sharing their information about events or safety issues. From this volume of data, the ASRS has released over 6,000 aviation safety alerts concerning potential hazards and safety concerns. The ASRS processes these reports, evaluates the information, and provides selected de-identified report information through the online ASRS Database at http:asrs.arc.nasa.gov. The NASA ASRS is also a founding member of the International Confidential Aviation Safety Systems (ICASS) group which is a collection of other national aviation reporting systems throughout the world. The ASRS model has also been replicated for application to improving safety in railroad, medical, fire fighting, and other domains. This presentation will discuss confidential, voluntary, and non-punitive reporting systems and their advantages in providing information for safety improvements.

Connell, Linda↗

NASA NTRS2020

International VLBI Service for Geodesy and Astrometry 2017+2018 Biennial Report

Since its creation in 1999, the International VLBI Service for Geodesy and Astrometry (IVS) has documented its progress and current status in the form of annual or biennial reports. The first sixteen years were recorded in the form of annual reports, while starting with the years 2015+2016 the rhythm was changed to two years. Hence, the 2017+2018 Biennial Report constitutes the second installment of the two-yearly reporting scheme, documenting the work of the IVS components for the calendar years 2017 and 2018. As a testament to its usefulness, the general structure of the reporting has remained stable over the years: the individual components of the IVS contributed short reports describing their numerous activities, progress, and future plans. Without the continued input from the VLBI groups of the international geodetic and astrometric community, this publication could not be compiled and the IVS itself would not be able to flourish. So, once again many thanks to all IVS components who contributed to this Biennial Report.

Armstrong, Kyla L.↗

NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRS2023

International VLBI Service for Geodesy and Astrometry 2021+2022 Biennial Report

Since its creation in 1999, the International VLBI Service for Geodesy and Astrometry (IVS) has documented its progress and current status in the form of annual or biennial reports. The first sixteen years were recorded in the form of annual reports. Starting in 2015/2016 the cadence was changed to two years; hence, this Biennial Report marks eight years of using the two-yearly reporting scheme. The general structure of the reporting has remained stable over the years: the individual components of the IVS contributed short reports describing their numerous activities, progress, and future plans. Without the continued input from the VLBI groups of the international geodetic and astrometric community, this publication could not be compiled and the IVS itself would not be able to flourish. So, once again many thanks to all IVS components who contributed to this Biennial Report

Space Geodesy↗

DOE OSTI2023

Design and License Application Development for TRISO-X (Final Scientific Technical Report)

This is the final progress report submitted by X-energy, LLC (XE) to the Department of Energy in support of cooperative agreement DE-NE0008745. This report provides a high-level summary of the work performed during the entire period of performance, running from August 24, 2018 – August 22, 2022. This span of time covers the original 3-year award and a one year no-cost extension. There were five tasks within this project: (1) project management, (2) systems engineering and studies, (3) TRISO-X Facility design, (4) facility license application development, and (5) support to application review. Detailed reporting during execution of the project was provided by a total of 16 quarterly reports, voluntary monthly update presentations, and annual summary presentations. Technical work products include 103 X-energy technical reports, 38 subcontractor (Centrus technical reports), 75 Nuclear Criticality Safety Evaluations/Calculation reports, and 272 miscellaneous design documents (e.g., Engineering Service Orders, Engineering Component Specifications, Procedures, Guidelines/Policies, Design and Interface Requirements documents, and Drawings). All 29 of the X Energy milestones/deliverables were met early or on time and are archived in the DOE Office of Nuclear Energy’s Program Information Control System: Nuclear Energy under Fiscal Year 2018, Work Breakdown Structure F.OA – Industry FOA FY 2018 Awards, F.03 – X-Energy TRISO-X Project. All other work products are available to DOE upon request.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Bridging the time scale in exascale computing of chemical systems (Final Technical Report)

This report summarizes the work carried out with support of the United States Department of Energy under Award DE-SC0019441. The theme of this project was to develop and apply methods that allowed for the acceleration of atomistic calculations, particularly in challenging areas such as multiphase systems, electrified interfaces, uncertainty estimation, and applications requiring chemical accuracy, which tend to be applications where simulation time is severely bottlenecked by the computational time requirements. Much of the focus was on the application of emerging machine-learning methodologies, although a wide range of methodologies were employed. This report has two major sections. The first focuses on the methodological advances themselves. Within this part, we report a number of major advances, a few examples of which are described here. We report the first machine-learning scheme for the acceleration of electronically grand-canonical calculations (that is, those applicable to electrochemistry). We report new methods of performing transfer learning, in which physics-based priors can be used to provide predictions, often with uncertainty estimates, of images well outside of training sets; we also offer ways to fine-tune these transfer-learning models. We provide a new systematic means to generate and apply minimal training data sets to very large (10,000’s of atoms) systems, with only small training sets appropriate for electronic structure. We developed new methodologies to integrate surface vibrations into surface adsorption calculations. We made advances to the applicability of diffusion Monte Carlo methods to allow (learned) force prediction, finite-size error correction, and force-free means of searching for transition states. We integrated machine-learned atomistic predictions into mechanism generation codes. Additionally, we released new software including AmpTorch, a modernized version of our original atomistic machine-learning code Amp. The second part of this report focuses on the scientific applications that accompanied, and were often enabled by, the methodological advances described earlier. A few examples follow, but full details are in the individual chapters of the report. For example, we developed a general theory of phonon-induced friction on molecular adsorbates. We showed fundamentally how solvent influences the adsorption and desorption process and how it differs from the processes typically involved at the solid–gas interface, making aqueous-phase and electrocatalysis different from traditional thermocatalysis. We examined how metal–insulator and magnetic transitions can be probed, and accelerated exciton dynamics via Frenkel Hamiltonian parameters. We showed that the nearsighted force-training approach, developed within this project, can predict both the stability and reactivity of large nanoparticles, and can also lead to insights on catalyst coverage on binding energies and entropies. These applied studies, which generally integrated with our method development, allowed us to push forward the theoretical understanding of several reaction classes.

08 HYDROGEN↗

DOE OSTI2019

Energy Storage Data Reporting in Perspective—Guidelines for Interpreting the Performance of Electrochemical Energy Storage Systems

Due to the tremendous importance of electrochemical energy storage, numerous new materials and electrode architectures for batteries and supercapacitors have emerged in recent years. Correctly characterizing these systems requires considerable time, effort, and experience to ensure proper metrics are reported. Many new nanomaterials show electrochemical behavior somewhere in between conventional double-layer capacitor and battery electrode materials, making their characterization a non-straightforward task. It is understandable that some researchers may be misinformed about how to rigorously characterize their materials and devices, which can result in inflation of their reported data. Additionally, this is not uncommon considering the current state of the field nearly requires record breaking performance for publication in high-impact journals. Incorrect characterization and data reporting misleads both the materials and device development communities, and it is the shared responsibility of the community to follow rigorous reporting methodologies to ensure published results are reliable to ensure constructive progress. This tutorial aims to clarify the main causes of inaccurate data reporting and to give examples of how researchers should proceed. The best practices for measuring and reporting metrics such as capacitance, capacity, coulombic and energy efficiencies, electrochemical impedance, and the energy and power densities of capacitive and pseudocapacitive materials are discussed.

25 ENERGY STORAGE↗