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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Science Use Case Design Patterns for Autonomous Experiments

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This paper introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further offers an overview of the 12 defined patterns and 4 examples of patterns of 2 different pattern classes. It also provides insight into building solutions from these patterns. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

Engelmann, Christian↗
DOE OSTI2016

2016 High Performance Computing Annual Report

Sandia National Laboratories’ California site is celebrating its 60th anniversary (1956 to 2016), and high performance computing has been a key enabler for its scientists and engineers throughout much of its history. Since its founding, Sandia California has helped pioneer the use of HPC platforms including hosting Sandia’s first Cray-1 supercomputer in the 1970s and supporting development of scalable cluster computing platforms to create a new paradigm for cost-effective supercomputing in the 1990s. Recent decades of investment in creation of scalable application frameworks for scientific computing have also enabled new generations of modeling and simulation codes. These resources have facilitated computational analysis of complex phenomena in diverse applications spanning national defense, energy, and homeland security. Today, Sandia California researchers work with partners in academia, industry, and national labs to evolve the state-of-the-art in HPC, modeling, and data analysis (including foundational capabilities for exascale computing platforms) and apply them in transformational ways. Research efforts include mitigating the effects of silent hardware failures that can jeopardize the results of large-scale computations, developing exascale-capable asynchronous task-parallel programming models and runtime systems, formulating new techniques to better explore and analyze extreme-scale data sets, and increasing our understanding of materials and chemical sciences which has applications spanning nuclear weapons stockpile stewardship to more efficient automobile engines. The following section highlights some of these research and applications projects and further illustrates the breadth of our HPC capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The Fabric for Frontier Experiments Project at Fermilab

The FabrIc for Frontier Experiments (FIFE) project is a new, far-reaching initiative within the Fermilab Scientific Computing Division to drive the future of computing services for experiments at FNAL and elsewhere. It is a collaborative effort between computing professionals and experiment scientists to produce an end-to-end, fully integrated set of services for computing on the grid and clouds, managing data, accessing databases, and collaborating within experiments. FIFE includes 1) easy to use job submission services for processing physics tasks on the Open Science Grid and elsewhere, 2) an extensive data management system for managing local and remote caches, cataloging, querying, moving, and tracking the use of data, 3) custom and generic database applications for calibrations, beam information, and other purposes, 4) collaboration tools including an electronic log book, speakers bureau database, and experiment membership database. All of these aspects will be discussed in detail. FIFE sets the direction of computing at Fermilab experiments now and in the future, and therefore is a major driver in the design of computing services worldwide.

Kirby, Michael↗
DOE OSTI2016

DragonView: Toward Understanding Network Interference in Dragonfly-based Supercomputers

Acquiring and maintaining high performance computing systems represents a substantial, long term investment. Therefore, it is paramount to optimize their utilization in order to maximize the return on investment and the impact on science and engineering. In this context, network congestion and inter-job interference are a major challenge as they can lead to significant systemwide performance degregation. This is especially pertinent in shared interconnects such as the dragonfly network, in which resources are shared by multiple jobs. Since many large-scale applications are communication-bound, a few communication heavy applications can have a large impact on the performance of all jobs and decrease the overall system throughput. In this paper, we describe a web-based visual analytics environment to study congestion and inter-job interference on dragonfly networks. The system enables network architects, system administrators and application developers to explore the potential impact of machine configuration, job placement policies and routing algorithms by visualizing and comparing ensembles of simulated workloads and real world data. We focus on the design of the system and describe the challenges, design decisions and the final implementation. Finally, we present two detailed case studies of prototypical analysis sessions by our stakeholders aimed at exploring the implications of different workloads and machine configurations using ensembles of network simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Electronic excitation spectra of molecular hydrogen in phase I from quantum Monte Carlo and many-body perturbation methods

Here, we study the electronic excitation spectra in solid molecular hydrogen (phase I) at ambient temperature and 5- to 90-GPa pressures using quantum Monte Carlo methods and many-body perturbation theory. In this range, the system changes from a wide-gap molecular insulator to a semiconductor, altering the nature of the excitations from localized to delocalized. Computed gaps and spectra agree with experiments, proving the ability to predict accurately band gaps of many-body systems in the presence of nuclear quantum and thermal effects.

08 HYDROGEN↗
DOE OSTI2016

SU-F-T-434: Development of a Fan-Beam Optical Scanner Using CMOS Array for Small Field Dosimetry

Purpose: To design and construct a second generation optical computed tomography (OCT) system using a fan-beam with a CMOS array detector for the 3D dosimetry with polymer gel and radiochromic solid dosimeters. The system was specifically designed for the small field dosimetry. Methods: The optical scanner used a fan-beam laser, which was produced from a collimated red laser beam (λ=620 nm) with a 15-degree laser-line generating lens. The fan-beam was sent through an index-matching bath which holds the sample stage and a sample. The emerging laser light was detected with a 2.54 cm-long CMOS array detector (512 elements). The sample stage rotated through the full 360 degree projection angles at 0.9-degree increments. Each projection was normalized to the unirradiated sample at the projection angle to correct for imperfections in the dosimeter. A larger sample could be scanned by using a motorized mirror and linearly translating the CMOS detector. The height of the sample stage was varied for a full 3D scanning. The image acquisition and motor motion was controlled by a computer. The 3D image reconstruction was accomplished by a fan-beam reconstruction algorithm. All the software was developed inhouse with MATLAB. Results: The scanner was used on both PRESAGE and PAGAT gel dosimeters. Irreconcilable refraction errors were seen with PAGAT because the fan beam laser line refracted away from the detector when the field was highly varying in 3D. With PRESAGE, this type of error was not seen. Conclusion: We could acquire tomographic images of dose distributions by the new OCT system with both polymer gel and radiochromic solid dosimeters. Preliminary results showed that the system was more suited for radiochromic solid dosimeters since the radiochromic dosimeters exhibited minimal refraction and scattering errors. We are currently working on improving the image quality by thorough characterization of the OCT system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Plasma facing components with capillary porous system and liquid metal coolant flow

Liquid metal can create a renewable protective surface on plasma facing components (PFC), with an additional advantage of deuterium pumping and the prospect of tritium extraction if liquid lithium (LL) is used and maintained below 450 °C, the temperature above which LL vapor pressure begins to contaminate the plasma. LM can also be utilized as an efficient coolant, driven by the Lorentz force created with the help of the magnetic field in fusion devices. Capillary porous systems can serve as a conduit of LM and simultaneously provide stabilization of the LM flow, protecting against spills into the plasma. Recently, a combination of a fast-flowing LM cooling system with a porous plasma facing wall (CPSF) was investigated [A. Khodak and R. Maingi, Nucl. Mater. Energy 26, 100935 (2021)]. The system takes an advantage of a magnetohydrodynamics velocity profile as well as attractive LM properties to promote efficient heat transfer from the plasma to the LL at low pumping energy cost, relative to the incident heat flux on the PFC. In the case of a disruption leading to excessive heat flux from the plasma to the LM PFCs, LL evaporation can stabilize the PFC surface temperature, due to high evaporation heat and apparent vapor shielding. The proposed CPSF was optimized analytically for the conditions of a fusion nuclear science facility [Kessel et al., Fusion Sci. Technol. 75, 886 (2019)]: 10 T toroidal field and 10 MW/m 2 peak incident heat flux. Finally, computational fluid dynamics analysis confirmed that a CPSF system with 2.5 mm square channels can pump enough LL so that no additional coolant is needed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Advanced Information Systems Technology for NASA Earth System Digital Twins (ESDT)

ESA and NASA have both started programs to design and develop Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. Earth System Digital Twins integrate diverse Earth and human activity models, continuous observations, and information system capabilities to provide unified, comprehensive representations and predictions that can be utilized for monitoring the health of the Planet, as well as for developing actionable information to support decision making. More generally, Digital Twins will help researchers better understand the fundamental Earth systems that impact everything from wildfires to climate change. This Townhall will first provide a short description of ESA’s, NASA’s and CNES’s current efforts in Digital Twins: • Destination Earth (DestinE) is the first initiative of the European Union to create a Digital Twin of the Earth, particularly focused on weather and climate, and as a coordinated effort between the European Centre for Medium-Range Weather Forecasts (ECMWF), ESA and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). • Additionally, ESA is developing several Digital Twin Earth Precursor Activities to study some of the key scientific and technical challenges associated with building a “Digital Twin Earth”. These include forests, hydrology, Antarctica, food systems, oceans, and climate hot spots Digital Twin prototypes. • NASA Earth Science Technology Office (ESTO)’s Advanced Information Systems Technology (AIST) Program has started an initiative in Earth System Digital Twins (ESDT), with 14 current projects in this area, developing various information systems technologies and prototypes that will help prepare the development of future NASA Digital Twins. • CNES is currently developing the concept of a Digital Twin Factory (DTF), which relies on a data lake, a high computing capability using clouds and/or HPC and has thematic algorithms and methodologies able to generate registered and coherent layers of information in order to enrich a datacube from which physical indicators can be computed spatially. NASA, ESA and CNES are also currently defining science use cases that will be presented during the townhall; those and a few short discussions of current projects will serve as a starting point to engage a dialogue about Digital Twins of the Earth with the IGARSS community.

earth science remote sensing; Information systems↗
DOE OSTI2019

Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks

Advances in computational science offer a principled pipeline for predictive modeling of cardiovascular flows and aspire to provide a valuable tool for monitoring, diagnostics and surgical planning. Such models can be nowadays deployed on large patient-specific topologies of systemic arterial networks and return detailed predictions on flow patterns, wall shear stresses, and pulse wave propagation. However, their success heavily relies on tedious pre-processing and calibration procedures that typically induce a significant computational cost, thus hampering their clinical applicability. Here, we put forth a machine learning framework that enables the seamless synthesis of non-invasive in-vivo measurement techniques and computational flow dynamics models derived from first physical principles. We illustrate this new paradigm by showing how one-dimensional models of pulsatile flow can be used to constrain the output of deep neural networks such that their predictions satisfy the conservation of mass and momentum principles. Once trained on noisy and scattered clinical data of flow and wall displacement, these networks can return physically consistent predictions for velocity, pressure and wall displacement pulse wave propagation, all without the need to employ conventional simulators. A simple post-processing of these outputs can also provide a relatively cheap and effective way for estimating Windkessel model parameters that are required for the calibration of traditional computational models. Finally, the effectiveness of the proposed techniques is demonstrated through a series of prototype benchmarks, as well as a realistic clinical case involving in-vivo measurements near the aorta/carotid bifurcation of a healthy human subject.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2009

A Future State for NASA Laboratories - Working in the 21st Century

The name "21 st Century Laboratory" is an emerging concept of how NASA (and the world) will conduct research in the very near future. Our approach is to carefully plan for significant technological changes in products, organization, and society. The NASA mission can be the beneficiary of these changes, provided the Agency prepares for the role of 21st Century laboratories in research and technology development and its deployment in this new age. It has been clear for some time now that the technology revolutions, technology "mega-trends" that we are in the midst of now, all have a common element centered around advanced computational modeling of small scale physics. Whether it is nano technology, bio technology or advanced computational technology, all of these megatrends are converging on science at the very small scale where it is profoundly important to consider the quantum effects at play with physics at that scale. Whether it is the bio-technology creation of "nanites" designed to mimic our immune system or the creation of nanoscale infotechnology devices, allowing an order of magnitude increase in computational capability, all involve quantum physics that serves as the heart of these revolutionary changes.

Kegelman, Jerome T.↗
DOE OSTI2025

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗
DOE OSTI2023

INTERSECT Architecture Specification: Use Case Design Patterns (V.0.9)

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This document introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further details the 12 defined patterns and provides insight into building solutions from these patterns. The document also describes the application of these patterns in the context of several INTERSECT autonomous laboratories. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A sub-pore model for multi-scale reaction–diffusion problems in porous media

Applications of reaction–diffusion systems in porous media pose a challenging problem for computational modeling approaches due to their multi-physics and multi-scale nature. The length scales usually span 3–4 orders of magnitude while physical phenomena involved include heat and mass transfer processes, and surface reactions. In this paper, a novel methodology that accounts for all the length scales and physical phenomena involved in a single framework is described. A length scale based dual approach is proposed – the larger pore channels (macro-pores) are resolved using conventional numerical techniques and a novel ‘sub-pore’ model is used to account for the unresolved pore channels (sub-pores) and the important physics therein. The porous network in the sub-pore system is composed of a fractal-like hierarchical system of straight cylindrical pores. Simplified governing equations for mass and energy transport are solved within the sub-pore system along with a reaction kinetics model to account for surface adsorption. An implicit coupling strategy is used to couple the macro-pore and the sub-pore systems so as to ensure conservation. The developed methodology is then applied to a few test cases and it is established that the proposed framework is necessary for problems where the adsorption time scale is much smaller than (diffusion-limited) or comparable to the diffusion time scale. Furthermore, it is also demonstrated that the framework can be potentially used to model the network of porous channels in its entirety thus significantly reducing computational costs.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Active workflow system for near real-time extreme-scale science. In: PPAA '14 Proceedings of the first workshop on Parallel programming for analytics applications

In recent years, streaming-based data processing has been gaining substantial traction for dealing with overwhelming data generated by real-time applications, from both enterprise sources and scientific computing. In this work, however, we look at an emerging class of scientific data with Near Real-Time (NRT) requirement, in which data is typically generated in a bursty fashion with the near real-time constraints being applied primarily between bursts, rather than within a stream. A key challenge for this types of data sources is that the processing time per data element is not uniform, and not always feasible to predict. Given the observations on the increasing unpredictability of compute load and system dynamics, this work looks to adapt streaming-based approach to the context of this new class of large experiments and simulations that have complex run-time control and analysis issues. In particular, we deploy a novel two-tier scheme for handling the increasing unpredictability of runtime behaviors: Instead of relying on determining what and where to run the scientific workflows beforehand or partial dynamically, the decision will also be adaptively enhanced online according to system runtime status. This is enabled by embedding workflow along with data streams. Specifically, we break data outputs generated from experiments or simulations into multiple self-describing "chunks", which we call active data objects. As such, if there is a transient hotspot observed, a data object with unfinished workflow pipeline can break its previous schedule and search for a least loaded location to continue the execution. Our preliminary experiment results based on synthetic workloads demonstrate the proposed active workflow system as a very promising solution by outperforming the state-of-the-art semi-dynamic workflow schedulers with an improved workflow completion time, as well as a good scalability.

Zhang, Yanwei↗
DOE OSTI2019

Material identification system

A method and apparatus for identifying a material in an object. An image of the object generated from energy passing through the object is obtained by a computer system. The computer system estimates attenuations for pixels in a sensor system from the image of the object to form estimated attenuations. The estimated attenuations represent a loss of the energy that occurs from the energy passing through the object. The computer system also identifies the material in the object using the estimated attenuations and known attenuation information for identifying the material in the object.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Challenges in large scale quantum mechanical calculations: Challenges in large scale quantum mechanical calculations

During the past decades, quantum mechanical methods have undergone an amazing transition from pioneering investigations of experts into a wide range of practical applications, made by a vast community of researchers. First principles calculations of systems containing up to a few hundred atoms have become a standard in many branches of science. The sizes of the systems which can be simulated have increased even further during recent years, and quantum-mechanical calculations of systems up to many thousands of atoms are nowadays possible. This opens up new appealing possibilities, in particular for interdisciplinary work, bridging together communities of different needs and sensibilities. In this review we will present the current status of this topic, and will also give an outlook on the vast multitude of applications, challenges and opportunities stimulated by electronic structure calculations, making this field an important working tool and bringing together researchers of many different domains.

Ratcliff, Laura E.↗