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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Porting OVERFLOW CFD Code to GPUs: To Hackathons and Beyond!

OVERFLOW is an overset, structured computational fluid dynamics (CFD) code written in Fortran which is widely used in the government, industry, and academia. Over the last several years the OVERFLOW developers have been working to port miniapps based on computationally expensive parts of OVERFLOW to run on GPUs, primarily using OpenACC. This effort started at our first hackathon in 2019 and since then the OVERFLOW team has attended two additional hackathons (virtually). These hackathon environments have provided a great place to collaborate with others and learn from experts. These learning experiences enabled porting two miniapps to run effectively on NVIDIA GPUs using OpenACC. The first miniapp focused on motifs found in the solver itself and the final ported version runs three times fast ona single V100 compared to a 40 core, dual-socket Intel Skylake node. The speed up in this solverminiapp required multiple design changes including increasing the amount of parallelism available and the amount of work performed in each kernel. The second miniapp focused on overset MPI communication, also saw significant speedups over the CPU implementation using a CUDA-aware MPI implementation through OpenACC. This presentation will discuss our experience at the hackathons, our process of porting the miniapps to run on the GPUs, and several lessons learned throughout.

OpenACC↗
NASA NTRS1995

Trainable Cataloging for Digital Image Libraries with Applications to Volcano Detection

Users of digital image libraries are often not interested in image data per se but in derived products such as catalogs of objects of interest. Converting an image database into a usable catalog is typically carried out manually at present. For many larger image databases the purely manual approach is completely impractical. In this paper we describe the development of a trainable cataloging system: the user indicates the location of the objects of interest for a number of training images and the system learns to detect and catalog these objects in the rest of the database. In particular we describe the application of this system to the cataloging of small volcanoes in radar images of Venus. The volcano problem is of interest because of the scale (30,000 images, order of 1 million detectable volcanoes), technical difficulty (the variability of the volcanoes in appearance) and the scientific importance of the problem. The problem of uncertain or subjective ground truth is of fundamental importance in cataloging problems of this nature and is discussed in some detail. Experimental results are presented which quantify and compare the detection performance of the system relative to human detection performance. The paper concludes by discussing the limitations of the proposed system and the lessons learned of general relevance to the development of digital image libraries.

digital image libraries, trainable cataloging↗
NASA NTRS2019

Evolving Management Strategies to Improve NASA Flagship's Cost and Schedule Performance: LUVOIR as a Case Study

The large ultraviolet optical infrared surveyor (LUVOIR) study process has brought to fruition an extremely exciting scientific mission concept. The 3.5 year LUVOIR study duration enabled an unprecedented level of scientific, engineering, and technology thoroughness prior to the Astro2020 Decadal. This detail also shed light on many technical and programmatic challenges for efficiently developing a mission of this scale within the context of NASA’s flagships cost and schedule performances to date. While NASA’s flagships perform exquisitely once on orbit, there is understandable growing frustration in their development cost and schedule overruns. We felt it incumbent upon ourselves to ask how we could improve on delivering LUVOIR (or any of NASA’s future flagships) on schedule and on budget, not just for the next mission, but for all NASA large strategic missions to come. We researched past and current NASA flagship’s lessons learned publications and other large government projects that pointed to some systemic challenges that will only grow with larger and more complex strategic missions. Our findings pointed us to some ways that could potentially evolve NASA’s current flagship management practices to help improve on their development cost and schedule performance despite their growing complexity. This paper briefly comments on the motivations for NASA’s flagships and on the science motivations for a LUVOIR-like mission. We argue the incentives for improving NASA’s flagships development cost and schedule performance. We review the specific additional challenges of NASA’s flagships to acknowledge their specific issues. We then examine the most repeated systemic challenges we found from previous NASA flagships and other large government projects lessons learned/observed. Lastly, we offer recommendations to tackle these repeated systemic challenges facing NASA’s flagships. The recommendations culminate into a proactive integrated development and funding framework to enable improving the execution of NASA’s future flagship’s cost and schedule performance.

Crooke, Julie A.↗
DOE OSTI2020

Facility Cybersecurity Framework Best Practices

Federal facilities are increasingly adopting automation and connecting to the Internet creating an energy-internet-of-things environment that converges operational technology (OT) and information technology (IT). Today's buildings increasingly weave together networked sensors and cyber and physical systems that enable data to be collected, aggregated, exchanged, stored and monetized in new ways. Building technological advances have created new energy technology, services, markets and value creation opportunities (e.g. transactive energy, two-way grid communications, machine learning, and increased use of renewable and distributed energy resources). But as larger data sets are being exchanged at faster speeds between an increasing number of OT systems, it becomes more difficult to protect the security of the data lifecycle and the physical equipment it interacts with. These challenges are especially difficult to overcome because the economic and environmental gain (interoperability, big data, social networks and ubiquitous information sharing) are driving these prominent trends in the digital age. Often cybersecurity is an afterthought. The U.S. Department of Energy’s (DOE) Federal Energy Management Program (FEMP) funded the Pacific Northwest National Laboratory (PNNL) to develop various cybersecurity tools, trainings, and reports to aid federal facility managers – and other building owners and operators – in better applying frameworks and lessons learned from the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF), risk management framework (RMF), DOE’s cybersecurity capability maturity model (C2M2), and a wide variety of industry best practices and guidance documents (i.e., NIST 800 series, Department of Defense United Facilities Criteria). This set of tools, collectively known as the FEMP Facility-Related Control System Cyber Toolkit (FRCS Cyber Toolkit)2, is focused on cybersecurity concerns from facility-related control systems and other operational technology (OT), such as industrial control systems (ICS). The FRCS Cyber Toolkit can be applied across six of the sixteen critical infrastructure sectors designated by the Department of Homeland Security, including government facilities, healthcare and public health, commercial facilities (e.g., public assembly, offices, lodging), financial services (e.g., banking and insurance), emergency services (e.g., fire and police stations), and information technology. With increasingly converged IT and OT systems, it is crucial to address OT cybersecurity considerations and assess how the seam of these two systems could impact the overall cybersecurity posture of a facility. The objective of this report is to provide an overview of the best possible method to use FRCS Cyber Toolkit (section 2.0) and distilled cybersecurity best practices for the federal facilities to address growing non-linear cyber threats (section 3.0). Recommendations in this document are aggregated from several NIST and other documents (see Appendix A for additional details).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Evolving Management Strategies to Improve NASA Flagship's Cost and Schedule Performance: LUVOIR as a Case Study

The LUVOIR study process has brought to fruition an extremely exciting scientific mission concept. The 3.5 year LUVOIR study duration enabled an unprecedented level of scientific, engineering, and technology thoroughness prior to the Astro2020 Decadal. This detail also shed light on many technical and programmatic challenges for efficiently developing a mission of this scale. While NASA's flagships perform exquisitely once on-orbit, there is understandable growing frustration in their development cost and schedule overruns. We felt it incumbent upon ourselves to ask how we could improve on delivering LUVOIR (or any of NASA's future flagships) on schedule and on budget, not just for the next mission, but for all NASA large strategic missions to come. We researched past and current NASA flagship's lessons learned publications and other large government projects that pointed to some systemic challenges that will only grow with larger and more complex strategic missions. Our findings pointed us to some ways that could potentially evolve NASA's current flagship management practices to help improve on their development cost and schedule performance despite their growing complexity.. This paper briefly comments on the science motivation for NASA's flagships and on the science motivation for a LUVOIR-like mission. We argue the motivation for improving NASA's flagships development cost and schedule performance. We review the specific challenges of NASA's flagships to acknowledge their specific issues. We then examine the most repeated systemic challenges we found from previous NASA flagship and other large government project lessons learned/observed. Lastly, we offer recommendations to tackle these repeated systemic challenges facing NASA's flagships. The recommendations culminate into a proactive integrated development and funding framework to enable improving the execution of NASA's future flagship's cost and schedule performance.

Crooke, Julie A.↗
NASA NTRSDate not supplied

Advancing Open Source Science Initiatives Through Public-Private Partnerships

Collaboration is fundamental to advancing open science within the science community. With the recent developments in technology and research, the establishment of formal partnerships between the private sector and government agencies are needed to bridge the knowledge gaps and expedite the time to actionable science. NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT) seeks to address this challenge by establishing non-reimbursable Space Act Agreements with industry leaders in cloud computing, artificial intelligence (AI) and machine learning. The purpose of these agreements is to advance open source science initiatives in the areas of data discovery, access and use of high value NASA science data sets on the cloud. As well as, jointly work on common research problems to accelerate the development and adoption of new AI technologies. Current success stories include co-locating NASA datasets from multiple science disciplines on one platform using Amazon Web Services Open Data Registry, developing AI Foundation Models for Science with IBM and co-hosting training workshops and tutorials for the science community aimed at providing hands-on experience with using NASA data and AI models on the cloud. In summary, we will present an overview of our partnerships supporting open source science initiatives, describe current activities and lessons learned that may be useful to others considering similar partnerships with the private sector.

Elizabeth Fancher↗
NASA NTRS2012

Shuttle Transportation System Case-Study Development

A case-study collection was developed for NASA's Space Shuttle Program. Using lessons learned and documented by NASA KSC engineers, analysts, and contractors, decades of information related to processing and launching the Space Shuttle was gathered into a single database. The goal was to provide educators with an alternative means to teach real-world engineering processes and to enhance critical thinking, decision making, and problem solving skills. Suggested formats were created to assist both external educators and internal NASA employees to develop and contribute their own case-study reports to share with other educators and students. Via group project, class discussion, or open-ended research format, students will be introduced to the unique decision making process related to Shuttle missions and development. Teaching notes, images, and related documents will be made accessible to the public for presentation of Space Shuttle reports. Lessons investigated included the engine cutoff (ECO) sensor anomaly which occurred during mission STS-114. Students will be presented with general mission infom1ation as well as an explanation of ECO sensors. The project will conclude with the design of a website that allows for distribution of information to the public as well as case-study report submissions from other educators online.

Ransom, Khadijah↗
NASA NTRS2006

Intelligence for Human-Assistant Planetary Surface Robots

The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area.

Hirsh, Robert↗
NASA NTRS2010

Failure Analysis at the Kennedy Space Center

History has shown that failures occur in every engineering endeavor, and what we learn from those failures contributes to the knowledge base to safely complete future missions. The necessity of failure analysis is at its apex at the end of one aged program and at the beginning of a new and untested program. The information that we gain through failure analysis corrects the deficiencies in the current vehicle to make the next generation of vehicles more efficient and safe. The Failure Analysis and Materials Evaluation Branch in the Materials Science Division at the Kennedy Space Center performs metallurgical, mechanical, electrical, and non-metallic materials failure analyses and accident investigations on both flight hardware and ground support equipment for the Space Shuttle, International Space Station, Constellation, and Launch Services Programs. This paper will explore a variety of failure case studies at the Kennedy Space Center and the lessons learned that can be applied in future programs.

Salazar, Victoria L.↗
NASA NTRS2010

Failure Analysis at the Kennedy Space Center

History has shown that failures occur in every engineering endeavor, and what we learn from those failures contributes to the knowledge base to safely complete future missions. The necessity of failure analysis is at its apex at the end of one aged program (i.e. Shuttle) and at the beginning of a new and untested program (i.e. Constellation). The information that we gain through failure analysis corrects the deficiencies in the current vehicle to make the next generation of vehicles more efficient and safe. The Failure Analysis and Materials Evaluation section in the Materials Science Division at the Kennedy Space Center performs metallurgical, mechanical, electrical, and non-metallic failure analysis and accident investigations on both flight hardware and ground support equipment (GSE) for the Shuttle, International Space Station, Constellation, and Launch Services Programs. This presentation will explore a variety of failure case studies at KSC and the lessons learned that can be applied in future programs.

Salazar, Victoria L.↗
DOE OSTI2023

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing

Abstract We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Lean Model-Based Systems Engineering on the NASA High-Density Vertiplex Subproject

The High Density Vertiplex (HDV) subproject of NASA’s Advanced Air Mobility (AAM) project adopted Model-Based Systems Engineering (MBSE)in July of 2020, prior to subproject formulation. A small and lean team of HDV Systems Engineers(SE) are utilizing MagicDraw to execute NASA SE processes via MBSE. The SEs learned how to use MagicDraw from scratch and HDV is the first project for which the SEs have utilized MagicDraw. This paper will demonstrate project technical execution via MBSE, utilizing the digital elements built into the SysML (Systems Modeling Language). SysML provides a model-centric means of carrying out the NASA SE common technical processes by providing tools for complete system modeling, including requirements and interface management and design capture. The authors also leverage and extend SysML to perform other SE tasks, such as Verification and Validation (V&V)tracking. MBSE has two main purposes for HDV: 1) documenting the subproject’s logical architecture for distribution outside of the subproject, 2) capturing the subproject’s physical architecture in a single-source-of-truth for use by the subproject’s members. This paper details the challenges, lessons learned, and solutions that were encountered in implementing MBSE in the first iteration on a multi-iteration, full-lifecycle design, build, fly project.

Demetrios Katsaduros↗
NASA NTRSDate not supplied

Lean Model-Based Systems Engineering on the NASA High-Density Vertiplex Subproject

The High Density Vertiplex (HDV) subproject of NASA’s Advanced Air Mobility (AAM) project adopted Model-Based Systems Engineering (MBSE) in July of 2020, prior to subproject formulation. A small and lean team of HDV Systems Engineers (SE) are utilizing MagicDraw to execute NASA SE processes via MBSE. The SEs learned how to use MagicDraw from scratch and HDV is the first project for which the SEs have utilized MagicDraw. This presentation will demonstrate project technical execution via MBSE, utilizing the digital elements built into the SysML (Systems Modeling Language). SysML provides a model-centric means of carrying out the NASA SE common technical processes by providing tools for complete system modeling, including requirements and interface management and design capture. The authors also leverage and extend SysML to perform other SE tasks, such as Verification and Validation (V&V) tracking. MBSE has two main purposes for HDV: 1) documenting the subproject’s logical architecture for distribution outside of the subproject, 2) capturing the subproject’s physical architecture in a single-source-of-truth for use by the subproject’s members. This presentation details the challenges, lessons learned, and solutions that were encountered in implementing MBSE in the first iteration on a multi-iteration, full-lifecycle design, build, fly project.

systems engineering↗
DOE OSTI2024

DECOVALEX-2023: Task E Final Report

This is the Task E final report for DECOVALEX-2023. Task E is focused on understanding thermal, two-phase hydrological, and mechanical (TH2M) processes, especially related to predicting brine migration in the excavation damaged zone around a heated excavation in salt. Salt is attractive as a disposal medium for radioactive waste because it is self-healing and is essentially impermeable and essentially non-porous in the far field (away from excavations). Investigation of the short-term (days to years) near-field (centimeters to tens of meters) behavior of salt is important for radioactive waste disposal because this early period strongly controls the amount of brine in a salt repository. Brine leads to corrosion of waste forms and waste packages, and possible dissolution of radionuclides with brine transport being a potential transport vector to the accessible environment. The main test case used in Task E is the ongoing Brine Availability Test in Salt (BATS) heater test located underground at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, New Mexico, USA. The Task was divided into a series of Steps. Step 0 was an introduction to processes in salt, that included matching historical unheated brine inflow data from boreholes at WIPP and matching temperature observations during BATS heater test 1a. Step 1 included validation of models against a thermo-poroelastic analytical solution relevant to heated boreholes in salt, and two-phase flow around an excavation in salt. Step 2 required all the individual components covered in steps 0 and 1 to come together to match observed brine inflow behavior during the BATS 1a heater test. There were a range of approaches from the teams, from mechanistic to prescriptive. Given the uncertainties in the problem, some teams used one- or two-dimensional models of the processes, while other teams included more geometrical complexity in three-dimensional models. The key learning points from Task E have been: • Heat conduction through salt typically requires non-linear thermal conductivity (as a function of temperature), but most models do a good job matching observations, given appropriate adjustments to the applied power and some thermocouple locations. • Thermal pressurization requires coupled thermal-hydrological-mechanical (THM) responses that consider the thermal expansion of the fluid and solid phases. • Initialization of two-phase flow models around a borehole or excavation in salt are more realistically represented as “wetting up”, rather than “drying down” (i.e., the initial state after excavation is mostly dry, rather than mostly wet). • The BATS 1a heater test includes a significant release of brine after the end of heating, which requires a large increase in permeability to recreate. Task E has been a great learning experience for all the teams involved, and feedback from the modeling teams has led to changes in the design of follow-on BATS experiments, which are now ongoing underground at WIPP. There was a balance throughout the task between freedom to model phenomena how each team saw fit, and prescriptiveness in problem design to bring the modeling teams closer together to allow attribution of smaller differences between models to different modeling choices. The modeling approaches seem to go through two phases: an early phase of discovery or testing, and a later phase of refinement and improvement. In future modeling efforts, different field data could be used (e.g., BATS 2) and more time should be included in the processes for teams to make multiple model refinement or even significant changes to their conceptual model or setup, based on lessons learned from the modeling exercise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2022

Pre-Installation Acceptance (PIA) Functional Performance of the Design Verification Test (DVT) Exploration Extra-vehicular Mobility Unit (xEMU)

In an effort that began with technology investment by NASA in a few key components during the Constellation Program and then evolved to demonstrate a packaged Portable Life Support System (PLSS) as part of the Advanced Exploration Systems (AES) Program, the next evolution of the PLSS is now a key component of the Exploration Extra-vehicular Mobility Unit (xEMU) and is assembled as a Design Verification Test (DVT) unit. The xEMU has been detailed with respect to completing a demonstration on the International Space Station (ISS) with support of units for initial lunar capability. The xEMU completed the Preliminary Design Review (PDR) with subsequent Safety Review Panel (SRP) Phase I reviews in 2019-2020. The objectives for DVT are to validate requirements, train the team, learn how to fabricate the hardware with appropriate process controls, assemble the hardware, test the hardware, determine the failure mechanisms/limits of the hardware design and buy down the most risk possible for the qualification and flight phases of the development. With completion of the assembly and initial functional testing of the DVT PLSS in laboratory ambient conditions and vacuum conditions the xEMU has progressed significantly into the DVT objectives. A key part of the test sequences for DVT and all future phases is the Pre-Installation Acceptance (PIA) functional testing which validates the performance of integrated systems including: primary thermal control, auxiliary thermal control, suit ventilation, primary oxygen, secondary oxygen, power distribution, as well as caution and warning all with respect to the applied requirements. This discussion will include an overview of the assembly, summary of the PIA functional testing, lessons learned, and corrective actions implemented moving forward into the remainder of the DVT phase for xEMU.

Colin Campbell↗
DOE OSTI2020

SUSTAINING NUCLEAR SECURITY REGIMES THROUGH CONTINUOUS LEARNING EXPERIENCES

As Member States plan, implement, and ultimately sustain their nuclear security regimes, human resource development supporting these regimes are paramount. Human resource development broadly includes programs addressing education, training, and knowledge management. The International Atomic Energy Agency’s Implementing Guide, Sustaining a Nuclear Security Regime, highlights the importance of national-level support for assigning resources that help ensure States are able to develop and retain sufficient human resources in the short, medium, and long term. Determining the resources needed to support education, training, and knowledge management is not an easy task, and knowledge management is a practice often overlooked when States plan for and allocate human resources for a nuclear security regime. The paper highlights the importance of implementing knowledge management practices as part of sustaining a nuclear security regime. Given the availability of secure web-based knowledge management tools, a nuclear security human resource development program should not depend solely on direct human interactions. To that end, the paper will offer an approach for planning and implementing a knowledge management system by using the U.S. Department of Energy/National Nuclear Security Administration’s Nuclear Smuggling Detection and Deterrence Knowledge Management Website as a case study. This example offers useful lessons learned for States considering or actively developing their own nuclear security knowledge management efforts and human resource development.

Tremonte, Matthew M.↗
NASA NTRS2012

An Altair Overview: Designing a Lunar Lander for 21st Century Human Space Exploration

Altair, the lunar lander element of NASA's Constellation program, was conducted in a different design environment than many other NASA projects of similar scope. Because of this relatively unique approach, there are a number of significant success stories that should be considered during the development of any future lunar landers or human spacecraft. This paper is divided into two separate themes; the first is the approach used during the conceptual design studies, including the systematic analysis cycles and the decision making process associated with each: and the second is a summary of the resulting lessons learned that were compiled after looking back at the lifetime of the Project. Altair was terminated before entering Phase B of its design, and was often criticized for being a very heavy and very large vehicle. While there was specific rationale for all of the decisions that led up to that configuration, future design cycles were specifically planned to re-address the mass challenge. Had the project continued, the deliberate, stepwise design process would have converged on an optimized lander design that balanced mass, risk, cost and capabilities. Some of the specific items that will be addressed in this paper include project development strategy, organizational approach and team dynamics, risk-informed design process, mission architecture constraints, mission key driving requirements, model-based systems engineering process, configuration studies, contingency considerations, subsystem overviews and key trade studies. The paper will conclude with a summary of the lessons identified during the Altair project and make suggestions for application to future studies.

Brown, Kendall K.↗
DOE OSTI2020

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.

Irle, Stephan↗