Foundational Research Gaps and Future Directions for Digital Twins

Foundational Research Gaps and Future Directions for Digital Twins is sponsored by National Institute of Standards and Technology (NIST). A program exploring the development of digital twins, emphasizing the importance of trustworthy data and models in digital representations of physical systems.

Foundational Research Gaps and Future Directions for Digital Twins Consensus/Advisory Activity Consensus/Advisory Activity An activity carried out by an appropriately knowledgeable and balanced ad hoc committee, the purpose of which is to provide formal advice on the matters posed in the statement of task for the activity.

These activities follow institutional policies and procedures to adhere to Section 15 of the Federal Advisory Committee Act (FACA). See all consensus/advisory activities Foundational Research Gaps and Future Directions for Digital Twins Digital twins promise to revolutionize decision-making across domains, from helping doctors develop personalized treatment plans to optimizing city-wide transportation systems.

But there are still challenges to overcome before the full potential of these technologies can be realized. This project explores future directions for digital twin technologies—and how to support this emerging field. Read our recent report, register for upcoming events, and download new resources below.

View the related VVUQ symposium. Foundational Research Gaps and Future Directions for Digital Twins Across multiple domains of science, engineering, and medicine, excitement is growing about the potential of digital twins to transform scientific research, industrial practices, and many aspects of daily life. A digital twin couples computational models with a physical counterpart to create a system...

A National Academies of Sciences, Engineering, and Medicine-appointed ad hoc committee will identify needs and opportunities to advance the mathematical, statistical, and computational foundations of digital twins in applications across science, medicine, engineering, and society. In so doing, the committee will address the following questions: Definitions and use cases: How are digital twins defined across communities?

What example use cases demonstrate the value of digital twins that are currently in deployment or development? Foundational mathematical, statistical and computational gaps: What foundational gaps and research opportunities exist in achieving robust reliable digital twins at scale? How do these foundational gaps or opportunities vary across communities and application domains?

What are the roles of data-driven learning and computational modeling (including mechanistic modeling) in achieving robust and reliable digital twins at scale? What data are needed to enable this modeling? What are the needs for validation, verification, and uncertainty quantification of digital twins, and how do these needs vary across communities?

Best practices for digital twin development and use: What best or promising practices for digital twins are emerging within and across application domains? What opportunities exist for translation of best practices across domains? What challenges exist for translation of best practices across domains?

How are difficult issues such as verification, validation, reproducibility, certification, security, ethics, consent, and privacy being addressed within domains? What lessons can be applied to other domains where digital twins are nascent? What use cases could advance awareness of and confidence in digital twins?

What are the key challenges and opportunities in the research, development, and application of advancements in digital twin development and application?

What roles could stakeholders (e.g., federal research funders, industry, academia, professional societies) play in advancing the development of rigorous scalable foundations of digital twins across scientific, medical, engineering and societal domains and in encouraging collaboration across communities?

The ad hoc committee will conduct three public workshops and other data-gathering activities to inform its findings, conclusions, and recommendations, which will be provided in the form of a consensus report.

The public workshops will present and discuss the opportunities (e.g. methods, practices, use cases) and challenges for the development and use of digital twins in three separate contexts: biomedical domains, Earth and environmental systems, and engineering.

These workshops will bring together diverse stakeholders and experts to address the following topics: Definitions and taxonomy of digital twins within the specified domain, including identification of exemplar use cases of digital twins; Current methods and promising practices for digital twin development and use at various levels of complexity; Key technical challenges and opportunities in the near and long term for digital twin development and use; and Opportunities for translation of promising practices from other fields and domains.

The presentations and discussions during the workshops will be summarized and published in three separate Proceedings of a Workshop: In Brief documents.

National Institutes of Health National Science Foundation Board on Mathematical Sciences and Analytics Major units and sub-units Center for Advancing Science and Technology Division on Earth and Life Studies Division on Engineering and Physical Sciences National Academy of Engineering Office of Programs Computer Science and Telecommunications Board Board on Atmospheric Sciences and Climate Board on Mathematical Sciences and Analytics Physical Sciences, Systems, and Infrastructure Program Area Review of the Long-Term Operations of the Central Valley Project and the State Water Project: Cycle 2 Consensus/Advisory Activity Future of Battery Technology Options for Defense Applications Consensus/Advisory Activity Assessment of Technical and Scientific Capabilities at NASA Goddard Space Flight Center Consensus/Advisory Activity Webinar Series: Leadership in Serious Illness Care Community-Driven Green Infrastructure Strategies for Energy Parks in the United States – Issue Paper Individually-Authored Product Planning and Building the Electricity System of the Future: A Workshop Integration of Artificial Intelligence in the Electricity System: A Workshop Space, Security, and Conflicts Our peer-reviewed reports present the evidence-based consensus of committees of experts.

Explore the Latest News and Stories The latest news and stories, with context you can trust. Seminar/Webinar/Lecture Series Stay in the loop with can’t-miss sessions, live events, and activities happening over the next two days. Annual State of the Science Address – June 2 Join NAS President Marcia McNutt for a discussion on the U.S. research enterprise and global science leadership.

Grants, Fellowships and Awards Science Communication Awards Congressional and Government Affairs Connecting policymakers with the National Academies Answers to everyday science and health questions Learn about membership to the three Academies Information on building access, visitor requirements, and facility operations. Karen E.

Willcox is Director of the Oden Institute for Computational Engineering and Sciences, Associate Vice President for Research, and Professor of Aerospace Engineering and Engineering Mechanics at the University of Texas at Austin. She is also External Professor at the Santa Fe Institute. At UT, she holds the W.

A. “Tex” Moncrief, Jr. Chair in Simulation-Based Engineering and Sciences and the Peter O'Donnell, Jr. Centennial Chair in Computing Systems. Before joining the Oden Institute in 2018, she spent 17 years as a professor at the Massachusetts Institute of Technology, where she served as the founding Co-Director of the MIT Center for Computational Engineering and the Associate Head of the MIT Department of Aeronautics and Astronautics.

Prior to joining the MIT faculty, she worked at Boeing Phantom Works with the Blended-Wing-Body aircraft design group. She is a Fellow of the Society for Industrial and Applied Mathematics (SIAM), a Fellow of the American Institute of Aeronautics and Astronautics (AIAA), and in 2017 was appointed Member of the New Zealand Order of Merit (MNZM) for services to aerospace engineering and education.

In 2022 she was elected to the National Academy of Engineering (NAE). Willcox is at the forefront of the development and application of computational methods for design, optimization and control of next-generation engineered systems. A number of her active research projects and collaborations with industry are developing core mathematical and computational capabilities to achieve predictive digital twins at scale.

Derek Bingham is a Professor and Chair of the Department Statistics and Actuarial Science at Simon Fraser University. He received his PhD from the Department of Mathematics and Statistics at Simon Fraser University in 1999. After graduation he joined the Department of Statistics at the University of Michigan.

He moved back to Simon Fraser in 2003 as the Canada Research Chair in Industrial Statistics. He has recently completed a three-year term as Chair for the Natural Sciences and Engineering Research Council of Canada’s Evaluation Group for Mathematical and Statistical Sciences. The focus of his current research is developing statistical methods for combining physical observations with large-scale computer simulators.

This includes new methodology for Bayesian computer model calibration, emulation, uncertainty quantification and experimental design. Dr. Bingham’s work is motivated by real-world applications. Recent collaborations have been with scientists at U.S. national laboratories (e.g., Los Alamos National Lab), U.S. Department of Energy sponsored projects (Center for Exascale Radiation Transport), and Canadian Nuclear Labs.

Julianne Chung is an Associate Professor in the Department of Mathematics at Emory University. Prior to joining Emory in 2022, she was an Associate Professor in the Department of Mathematics and part of the Computational Modeling and Data Analytics Program at Virginia Tech.

From 2011-2012, she was an Assistant Professor at the University of Texas at Arlington and from 2009-2011 an NSF Mathematical Sciences Postdoctoral Research Fellow at the University of Maryland at College Park. She received her PhD in 2009 in the Department of Math and Computer Science at Emory University, during which she was supported by a Department of Energy Computational Science Graduate Fellowship.

She has received many prestigious awards including the Frederick Howes Scholar in Computational Science award, an NSF CAREER award, and an Alexander von Humboldt Research Fellowship. Her research interests include numerical methods and software for computing solutions to large-scale inverse problems, such as those that arise in imaging applications.

Dr. Chung is vice president and Chief Data Officer and is an associate professor in Radiation Oncology and Diagnostic Imaging. Her clinical practice is focused on CNS malignancies and her computational imaging lab has a research focus on quantitative imaging and computational modeling to detect and characterize tumors and toxicities of treatment to enable personalized cancer treatment.

Internationally, Dr. Chung is actively involved in multidisciplinary efforts to improve the generation and utilization of high quality, standardized imaging to facilitate quantitative imaging integration for clinical impact across multiple institutions, including Vice Chair of the Radiological Society of North America (RSNA) Quantitative Imaging Biomarker Alliance (QIBA) and Co-Chair of the Quantitative Imaging for Assessment of Response in Oncology Committee of the International Commission on Radiation Units and Measurements (ICRU).

Beyond her clinical, research and administrative roles, Dr. Chung enjoys serving as an active educator and mentor with a passion to support the growth of diversity, equity and inclusion in STEM, including her role as Chair of Women in Cancer (http://www. womenincancer.

com), a non-for-profit organization that is committed to advancing cancer care by encouraging the growth, leadership and connectivity of current and future oncologists, trainees and medical researchers. Her recent publications include work on building digital twins for clinical oncology.

Dr. Carolina Cruz-Neira is a pioneer in the areas of virtual reality and interactive visualization, having created and deployed a variety of technologies that have become standard tools in industry, government and academia. She is known world-wide for being the creator of the CAVE virtual reality system.

She has dedicated a part of her career to transfer research results into daily use by spearheading several Open Source initiatives to disseminate and grow VR technologies and by leading entrepreneurial initiatives to commercialize research results. She has over 100 publications as scientific articles, book chapters, magazine editorials and others. She has been awarded over $75 million in grants, contracts, and donations.

She is also recognized for having founded and led very successful virtual reality research centers, like the Virtual Reality Applications Center at Iowa State University, the Louisiana Immersive Technologies Enterprise and now the Emerging Analytics Center. She has been named one of the top innovators in virtual reality and one of the top three greatest women visionaries in this field.

BusinessWeek magazine identified her as a “rising research star” in the next generation of computer science pioneers; she has been inducted as a member of the National Academy of Engineering, an ACM Computer Pioneer, received the IEEE Virtual Reality Technical Achievement Award and the Distinguished Career Award from the International Digital Media & Arts Society among other national and international recognitions.

She had given numerous keynote addresses and has been the guest of several governments to advise on how virtual reality technology can help to give industries a competitive edge leading to regional economic growth. She has appeared in numerous national and international TV shows and podcasts as an expert on her discipline and several documentaries have been produced about her life and career.

She has several ongoing collaborations in advisory and consulting capacities on the foundational role of virtual reality technologies with respect to digital twins. Conrad J.

Grant is the Chief Engineer for the Johns Hopkins University Applied Physics Laboratory, the nation’s largest University Affiliated Research Center, performing research and development on behalf of the Department of Defense, the intelligence community, the National Aeronautics and Space Administration, and other federal agencies.

He previously served for over a decade as the Head of the APL Air and Missile Defense Sector where he led 1200 staff developing advanced air and missile defense systems for the U.S. Navy and the Missile Defense Agency.

Mr. Grant has extensive experience in the application of systems engineering to the design, development, test and evaluation, and fielding of complex systems involving multi-sensor integration, command and control, human-machine interfaces, and guidance and control systems.

Mr. Grant’s engineering leadership in APL prototype systems for the Navy is now evidenced by capabilities on board over 100 cruisers, destroyers, and aircraft carriers of the U.S. Navy and its Allies. He has served on national committees including as a technical advisor on studies for the Naval Studies Board (NSB) of the National Academies as well as membership on the U.S. Strategic Command Senior Advisory Group (SAG).

He is a member of the program committees for the Department of Electrical and Computer Engineering (ECE) and the Engineering for Professionals Systems Engineering Program of the Johns Hopkins University Whiting School of Engineering.

Mr. Grant earned a Bachelor of Science in Physics from the University of Maryland, College Park, a Master of Science in Applied Physics and a Master of Science in Computer Science from the Johns Hopkins University, Whiting School of Engineering. James L. Kinter is Director of the Center for Ocean-Land-Atmosphere Studies (COLA) at George Mason University (GMU), where he oversees basic and applied climate research conducted by the Center.

Dr. Kinter’s research includes studies of atmospheric dynamics and predictability on intra-seasonal and longer time scales, particularly the prediction of Earth’s climate using numerical models of the coupled ocean-atmosphere-land system.

Dr. Kinter is a tenured Professor of Climate Dynamics in the Atmospheric, Oceanic and Earth Sciences (AOES) department of the College of Science at GMU, where he has responsibilities for teaching climate predictability and climate change.

After earning his doctorate in geophysical fluid dynamics at Princeton University in 1984, Dr. Kinter served as a National Research Council Associate at NASA Goddard Space Flight Center, and as a faculty member of the University of Maryland prior to helping to create COLA.

Dr. Kinter, a Fellow of the American Meteorological Society, has served on many national and international review panels for both scientific research programs and supercomputing programs for computational climate modeling. Dr. Kinter has served on three previous National Academies committees. L.

Ruby Leung is a Battelle Fellow at Pacific Northwest National Laboratory. Her research broadly cuts across multiple areas in modeling and analysis of climate and water cycle including orographic precipitation, monsoon climate, extreme events, land surface processes, landatmosphere interactions, and aerosol-cloud interactions.

Dr. Leung is the Chief Scientist of the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM), a major effort involving over 100 earth and computational scientists and applied mathematicians to develop state-of-the-art capabilities for modeling human-Earth system processes on DOE’s next generation high performance computers.

She has organized several workshops sponsored by Department of Energy, National Science Foundation, National Oceanic and Atmospheric Administration, and National Aeronautics and Space Administration to define gaps and priorities for climate research. She is a member of the Board on Atmospheric Sciences and Climate (BASC), National Academies of Sciences, Engineering, and Medicine and an editor of the AMS Journal of Hydrometeorology.

She has published over 450 papers in peer-reviewed journals. Dr. Leung is an elected member of the National Academy of Engineering and Washington State Academy of Sciences. She is also a fellow of the American Meteorological Society (AMS), American Association for the Advancement of Science (AAAS), and American Geophysical Union (AGU).

She is the recipient of the AGU Global Environmental Change Bert Bolin Award and Lecture in 2019, the AGU Atmospheric Science Jacob Bjerknes Lecture in 2020, and the AMS Hydrologic Sciences Medal in 2022. She was awarded the DOE Distinguished Scientist Fellow in 2021. She received a BS in Physics and Statistics from Chinese University of Hong Kong and an MS and PhD in Atmospheric Sciences from Texas A&M University.

Parviz Moin (NAS/NAE) is the Franklin P. and Caroline M. Johnson Professor of Mechanical Engineering and the director of the Center for Turbulence Research (CTR) at Stanford University.

He was the founding director of the Institute for Computational and Mathematical Engineering and he directed the Department of Energy’s ASCI and PSAAP centers. Dr. Moin pioneered the use of direct numerical simulation and large eddy simulation techniques for the study of the physics, and reduced order modeling of multi-physics turbulent flows.

His current research interests include predictive simulation of aerospace systems, hypersonic flows, multi-phase flows, propulsion, numerical analysis for multi-scale problems, and flow control. Dr. Moin is the co- editor of the Annual Review of Fluid Mechanics and associate editor of the Journal of Computational Physics. Amongst his awards are the American Physical Society (APS) Fluid Dynamics Prize and AIAA Fluid Dynamics Award.

Dr. Moin is a member of the National Academy of Sciences, National Academy of Engineering, and the Royal Spanish Academy of Engineering. He is a fellow of APS and AIAA, and the American Academy of Arts and Sciences. Dr. Moin received a Ph.

D. in mechanical engineering from Stanford University. Lucila Ohno-Machado, MD, PhD, MBA, has been appointed deputy dean for biomedical informatics and will lead the newly created free-standing Section for Biomedical Informatics and Data Science at Yale School of Medicine starting 1/1/23.

She is currently health sciences associate dean for informatics and technology, founding chief of the Division of Biomedical Informatics in the Department of Medicine, and distinguished professor of medicine at the University of California San Diego (UCSD). She also is founding chair of the UCSD Health Department of Biomedical Informatics and founding faculty of the UCSD Halicioglu Data Science Institute in La Jolla, California.

She received her medical degree from the University of São Paulo, Brazil; her MBA from the Escola de Administração de São Paulo, Fundação Getúlio Vargas, Brazil; and her PhD in medical information sciences and computer science at Stanford University. She has led informatics centers that were funded by various NIH initiatives and by agencies such as AHRQ, PCORI, and NSF.

Dr. Ohno-Machado organized the first large-scale initiative to share clinical data across five UC medical systems and later extended it to various institutions in California and around the country. Prior to joining UCSD, she was distinguished chair in biomedical informatics at Brigham and Women’s Hospital, and faculty at Harvard Medical School and at MIT’s Health Sciences and Technology Division.

She is an elected member of the National Academy of Medicine, the American Society for Clinical Investigation, the American Institute for Medical and Biological Engineering, the American College of Medical Informatics, and the International Academy of Health Sciences Informatics. She is a recipient of the American Medical Informatics Association leadership award, as well as the William W.

Stead Award for Thought Leadership in Informatics. She serves on several advisory boards for national and international agencies. Dr. Colin James Parris’ 35+ year career has seen him achieve great academic and professional success while attending and leading some of the most prestigious academic and business institutions in America and the world.

His career has been centered on the development and enhancement of digital transformation across multiple industries (telecommunications, banking, retail, aviation, energy) in billion-dollar companies, as well as advocating/evangelizing STEM advancement across minority communities.

As GE Digital’s Chief Technology Officer, Dr. Parris leads teams that work to leverage technologies and capabilities across GE to accelerate business impact and create scale advantage for digital transformation. He also champions strategic innovations and identifies and evaluates new, breakthrough technologies and capabilities to accelerate innovative solutions to solve emerging customer problems.

Dr. Parris created and leads the Digital Twin Initiative across GE. He previously held the position of Vice President, Software and Analytics Research at GE Research in Niskayuna, NY. Prior to joining GE, Dr. Parris worked at IBM where he was an executive for 16 years in roles that spanned research, software development, technology management, and P&L management.

He was the Vice President, System Research at the IBM Thomas J. Watson Research Division, the Vice President Software Development for IBM's largest system software development lab (6,000+ developers worldwide), Vice President of Corporate Technology, and the Vice President and General Manager of IBM Power Systems responsible for the company's $5B+ Unix System and Software business.

Dr. Parris holds a PhD, Electrical Engineering from the University of California, Berkeley; an MS from Stanford University; an MS, Electrical Engineering and Computer Science from the University of California, Berkeley and a BS, Electrical Engineering from Howard University.

Irene Qualters serves as the Associate Laboratory Director for Simulation and Computation at Los Alamos National Laboratory, a U.S. Department of Energy national laboratory.

She previously served as a Senior Science Advisor in the Computing and Information Science and Engineering (CISE) Directorate of the National Science Foundation (NSF), where she had responsibility for developing NSF’s vision and portfolio of investments in high performance computing, and has played a leadership role in interagency, industry, and academic engagements to advance computing.

Prior to her NSF career, Irene had a distinguished 30-year career in industry, with a number of executive leadership positions in research and development in the technology sector. During her 20 years at Cray Research, she was a pioneer in the development of high performance parallel processing technologies to accelerate scientific discovery.

Subsequently as Vice President, she led Information Systems for Merck Research Labs, focusing on software, data and computing capabilities to advance all phases of pharmaceutical R&D. Prof. Ines Thiele is the principal investigator of the Molecular Systems Physiology group at the University of Galway, Ireland. Her research aims to improve the understanding of how diet influences human health.

Therefore, she uses a computational modelling approach, termed constraint-based modelling, which has gained increasing importance in systems biology. Her group builds comprehensive models of human cells and human-associated microbes; then employs them together with experimental data to investigate how nutrition and genetic predisposition can affect one's health.

In particular, she is interested in applying her computational modelling approach for better understanding of inherited and neurodegenerative diseases. Dr. Thiele has been pioneering models and methods allowing large-scale computational modelling of the human gut microbiome and its metabolic effect on human metabolism. She earned her PhD in bioinformatics from the University of California, San Diego, in 2009.

She was an Assistant and Associate Professor at the University of Iceland (2009 - 2013), and Associate Professor at the University of Luxembourg (2013-2019). In 2013, Dr. Thiele received the ATTRACT fellowship from the Fonds National de la Recherche (Luxembourg). In 2015, she was elected as EMBO Young Investigator.

In 2017, she was awarded the prestigious ERC starting grant. In 2020, she was named a highly cited researcher by Clarivate, and received the NUI Galway President’s award in research excellence. She is an author of over 100 international scientific papers and reviewer for multiple journals and funding agencies.

Dr. Conrad Tucker is an Arthur Hamerschlag Career Development Professor of Mechanical Engineering at Carnegie Mellon University and holds courtesy appointments in Machine Learning, Robotics, Biomedical Engineering, and CyLab Security and Privacy. His research focuses on employing Machine Learning (ML)/Artificial Intelligence (AI) techniques to enhance the novelty and efficiency of engineered systems.

His research also explores the challenges of bias and exploitability of AI systems and the potential impacts on people and society. Dr. Tucker has served as PI/Co-PI on federally/non-federally funded grants from the National Science Foundation, the Air Force Office of Scientific Research, the Defense Advanced Research Projects Agency, the Army Research Laboratory, the Bill and Melinda Gates Foundation, among others.

In February 2016, he was invited by National Academy of Engineering (NAE) President Dr. Dan Mote, to serve as a member of the Advisory Committee for the NAE Frontiers of Engineering Education Symposium. He is currently serving as a Commissioner on the U.S. Chamber of Commerce Artificial Intelligence Commission on Competitiveness, Inclusion, and Innovation. Dr. Tucker received his Ph.

D. , M. S.

(Industrial Engineering), and MBA degrees from the University of Illinois at Urbana-Champaign, and his B. S. in Mechanical Engineering from Rose-Hulman Institute of Technology.

Rebecca Willett is a Professor of Statistics and Computer Science at the University of Chicago. Her research is focused on machine learning, signal processing, and large-scale data science.

Willett received the National Science Foundation CAREER Award in 2007, was a member of the DARPA Computer Science Study Group, received an Air Force Office of Scientific Research Young Investigator Program award in 2010, was named a Fellow of the Society of Industrial and Applied Mathematics in 2021, and was named a Fellow of the IEEE in 2022.

She is a co-principal investigator and member of the Executive Committee for the Institute for the Foundations of Data Science, helps direct the Air Force Research Lab University Center of Excellence on Machine Learning, and currently leads the University of Chicago’s AI+Science Initiative.

She serves on advisory committees for the National Science Foundation’s Institute for Mathematical and Statistical Innovation, the AI for Science Committee for the US Department of Energy’s Advanced Scientific Computing Research program, the Sandia National Laboratories Computing and Information Sciences Program, and the University of Tokyo Institute for AI and Beyond.

She completed her PhD in Electrical and Computer Engineering at Rice University in 2005 and was an Assistant then tenured Associate Professor of Electrical and Computer Engineering at Duke University from 2005 to 2013. She was an Associate Professor of Electrical and Computer Engineering, Harvey D. Spangler Faculty Scholar, and Fellow of the Wisconsin Institutes for Discovery at the University of Wisconsin-Madison from 2013 to 2018.

Prof. Xinyue Ye is Fellow of American Association of Geographers (AAG) and Fellow of Royal Geographical Society (with IBG), holding Harold L. Adams Endowed Professorship in Department of Landscape Architecture and Urban Planning & Department of Geography at Texas A&M University-College Station (TAMU), USA.

He directs the focus of transportation in the PhD program of Urban and Regional Science at TAMU, and is the Interim Director of Center for Housing and Urban Development. His research focuses on geospatial artificial intelligence, geographic information system, and smart cities. Prof. Ye won the national first-place research award from University Economic Development Association.

He was the recipient of annual research awards from both computational science (New Jersey Institute of Technology) and Geography (Kent State University) as well as AAG Regional Development and Planning Distinguished Scholar Award. He was one of the top 10 young scientists named by The World Geospatial Developers Conference in 2021.

His work has been funded by National Science Foundation, National Institute of Justice, Department of Commerce, Department of Energy, and Department of Transportation. Prof. Ye is Editor-in-Chief of Computational Urban Science, an open access journal published by Springer. He also serves as the co-editor of Journal of Planning Education and Research, the flagship journal of Association of Collegiate Schools of Planning.

Former MyNAP users: You'll need to reset your password on your first login to MyAcademies. Click "Forgot password" below to receive a reset link via email. Having trouble?

Members of the National Academy of Sciences, National Academy of respective Academy portals. Password must be at least 8 characters I agree to receive emails from the National Academies While logged on as a guest, you can download any of our free PDFs on . You will remain logged in until you close your browser.

Yes, send me emails when similar titles are published Thank you for creating a MyAcademies account! Enjoy free access to thousands of National Academies' publications, a 10% discount off every purchase, and build your personal library. Enter the email address for your MyAcademies (formerly MyNAP) account to receive password reset instructions.

We sent password reset instructions to . Follow the link in that email to create a new password. Didn't receive it?

Check your spam folder or Password must be at least 8 characters Your password has been reset. Verify Your Email Address We sent a verification link to your email. Please check your inbox (and spam folder) and follow the link to verify your email address.

If you did not receive the email, you can request a new verification link below Resend Verification Email I agree to receive emails from the National Academies We respect your privacy and will never share your information.