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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A framework for inferring and analyzing pharmacotherapy treatment patterns

Background: To discover pharmacotherapy prescription patterns and their statistical associations with outcomes through a clinical pathway inference framework applied to real-world data. Methods: We apply machine learning steps in our framework using a 2006 to 2020 cohort of veterans with major depressive disorder (MDD). Outpatient antidepressant pharmacy fills, dispensed inpatient antidepressant medications, emergency department visits, self-harm, and all-cause mortality data were extracted from the Department of Veterans Affairs Corporate Data Warehouse. Results: Our MDD cohort consisted of 252,179 individuals. During the study period there were 98,417 emergency department visits, 1,016 cases of self-harm, and 1,507 deaths from all causes. The top ten prescription patterns accounted for 69.3% of the data for individuals starting antidepressants at the fluoxetine equivalent of 20-39 mg. Additionally, we found associations between outcomes and dosage change. Conclusions: For 252,179 Veterans who served in Iraq and Afghanistan with subsequent MDD noted in their electronic medical records, we documented and described the major pharmacotherapy prescription patterns implemented by Veterans Health Administration providers. Ten patterns accounted for almost 70% of the data. Associations between antidepressant usage and outcomes in observational data may be confounded. The low numbers of adverse events, especially those associated with all-cause mortality, make our calculations imprecise. Furthermore, our outcomes are also indications for both disease and treatment. Despite these limitations, we demonstrate the usefulness of our framework in providing operational insight into clinical practice, and our results underscore the need for increased monitoring during critical points of treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗
DOE OSTI2024

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

Markov decision process↗
DOE OSTI2026

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗
DOE OSTI2021

Adorym: a multi-platform generic X-ray image reconstruction framework based on automatic differentiation

We describe and demonstrate an optimization-based X-ray image reconstruction framework called Adorym. Our framework provides a generic forward model, allowing one code framework to be used for a wide range of imaging methods ranging from near-field holography to fly-scan ptychographic tomography. By using automatic differentiation for optimization, Adorym has the flexibility to refine experimental parameters including probe positions, multiple hologram alignment, and object tilts. It is written with strong support for parallel processing, allowing large datasets to be processed on high-performance computing systems. We demonstrate its use on several experimental datasets to show improved image quality through parameter refinement.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sapsan: Framework for Supernovae Turbulence Modeling with Machine Learning

Sapsan is a framework designed to make Machine Learning (ML) more accessible in the study of turbulence, with a focus on astrophysical applications. Sapsan includes modules to load, filter, subsample, batch, and split the data from hydrodynamic (HD) simulations for training and validation. Next, the framework includes built-in conventional and physically-motivated estimators that have been used for turbulence modeling. This ties into Sapsan’s custom estimator module, aimed at designing a custom ML model layer-by-layer, which is the core benefit of using the framework. To share your custom model, every new project created via Sapsan comes with pre-filled, ready-for-release Docker files. Furthermore, training and evaluation modules come with Sapsan as well. The latter, among other features, includes the construction of power spectra and comparison to established analytical turbulence closure models, such as a gradient model. Thus, Sapsan attempts to minimize the hard work required for data preparation and analysis, leaving one to focus on the ML model design itself.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Failure Analysis–Informed Risk Assessment Framework for Geological Carbon Storage Using Numerical Simulation and Machine Learning

Geological carbon storage (GCS) is recognized as a critical technology for achieving large-scale reductions in anthropogenic carbon dioxide (CO 2 ) emissions. Ensuring long-term containment and safety requires robust risk assessment frameworks that account for geological uncertainty and identify potential failure scenarios. Among various indicators, the area of review (AoR) serves as a key metric for evaluating storage performance, regulatory compliance, and monitoring design, as it delineates the spatial extent impacted by pressure buildup and plume migration. However, conventional AoR-based risk assessments typically perturb parameters within narrow uncertainty bounds, potentially overlooking rare but high-impact events arising from extreme geological conditions. In this study, we present a failure analysis–informed risk assessment framework for large-scale GCS projects to improve site prescreening and monitoring design. A suite of 300 numerical simulations was generated using stochastic geological models that vary five key parameters: net-to-gross ratio, anisotropy azimuth, porosity multiplier, permeability multiplier, and vertical-to-horizontal permeability ratio. Among these, 200 realizations represent normal geological uncertainty, while 100 additional cases explore extreme yet plausible conditions for failure-case analysis. The AoR was simulated and computed from pressure and CO 2 saturation fields, where the baseline AoR boundary, representing the extent predicted under typical geological uncertainty, was defined as the union of 200 normal-range simulations, and failure was identified when extreme-range cases exceeded this baseline. Results show that incorporating broader parameter uncertainty produces significantly larger AoR extents, underscoring the potential underestimation of risk under conventional uncertainty ranges. Furthermore, spatial probability maps derived from failure-induced AoR exceedance identify regions requiring enhanced monitoring attention. Various machine learning (ML)–based classifiers were developed to predict failure occurrence from geological parameters, with the random forest model achieving the highest performance (F1-score of 0.986). Consistent findings from correlation coefficient, feature importance, and Sobol sensitivity analyses reveal that low net-to-gross ratios and permeability multipliers are the dominant risk drivers, reflecting reduced reservoir connectivity and limited pressure dissipation. Altogether, these results provide a novel framework for risk-informed site prescreening and monitoring design that explicitly considers rare but high-impact geological scenarios in GCS projects.

25 ENERGY STORAGE↗
DOE OSTI2019

A conceptual evaluation framework for the water and sanitation for health facility improvement tool (Wash Fit)

Healthcare facilities (HCFs) in low- and middle-income countries frequently lack water, sanitation and hygiene (WASH) services that are adequate to implement infection prevention and control (IPC) practices, decrease healthcare-associated infections and antimicrobial resistance, and provide quality healthcare. The Water and Sanitation for Health Facility Improvement Tool (WASH FIT), initially published in 2017 and updated in 2018, is a risk-based, continuous improvement framework. The tool aims to improve WASH and related facility management and may contribute to quality of care (QoC) efforts. To date, there is no guidance available on how to monitor and evaluate the use of this tool nor is there rigorous evidence on its effectiveness. We developed a conceptual WASH FIT evaluation framework by drawing from the broader WASH, health systems strengthening, and QoC evidence base. This framework provides a common basis to plan, implement, monitor, and evaluate potential inputs, outputs, outcomes, and impacts from applying WASH FIT. Routine use of the tool, coupled with WASH infrastructure improvements as guided by the tool, can lead to better IPC practices, and may support improvements in occupational safety, QoC, global health security, and ultimately progress towards achieving Sustainable Development Goals 3 (good health and well-being) and 6 (clean water and sanitation).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A flexible framework for secure and efficient program obfuscation.

In this paper, we present a modular framework for constructing a secure and efficient program obfuscation scheme. Our approach, inspired by the obfuscation with respect to oracle machines model of [4], retains an interactive online protocol with an oracle, but relaxes the original computational and storage restrictions. We argue this is reasonable given the computational resources of modern personal devices. Furthermore, we relax the information-theoretic security requirement for computational security to utilize established cryptographic primitives. With this additional flexibility we are free to explore different cryptographic buildingblocks. Our approach combines authenticated encryption with private information retrieval to construct a secure program obfuscation framework. We give a formal specification of our framework, based on desired functionality and security properties, and provide an example instantiation. In particular, we implement AES in Galois/Counter Mode for authenticated encryption and the Gentry-Ramzan [13]constant communication-rate private information retrieval scheme. We present our implementation results and show that non-trivial sized programs can be realized, but scalability is quickly limited by computational overhead. Finally, we include a discussion on security considerations when instantiating specific modules.

Solis, John Hector↗
DOE OSTI2013

A modeling framework for investment planning in interdependent infrastructures in multi-hazard environments.

Currently, much of protection planning is conducted separately for each infrastructure and hazard. Limited funding requires a balance of expenditures between terrorism and natural hazards based on potential impacts. This report documents the results of a Laboratory Directed Research & Development (LDRD) project that created a modeling framework for investment planning in interdependent infrastructures focused on multiple hazards, including terrorism. To develop this framework, three modeling elements were integrated: natural hazards, terrorism, and interdependent infrastructures. For natural hazards, a methodology was created for specifying events consistent with regional hazards. For terrorism, we modeled the terrorist s actions based on assumptions regarding their knowledge, goals, and target identification strategy. For infrastructures, we focused on predicting post-event performance due to specific terrorist attacks and natural hazard events, tempered by appropriate infrastructure investments. We demonstrate the utility of this framework with various examples, including protection of electric power, roadway, and hospital networks.

Brown, Nathanael J. K.↗
DOE OSTI2013

Evaluation Framework and Analyses for Thermal Energy Storage Integrated with Packaged Air Conditioning

Few third-party guidance documents or tools are available for evaluating thermal energy storage (TES) integrated with packaged air conditioning (AC), as this type of TES is relatively new compared to TES integrated with chillers or hot water systems. To address this gap, researchers at the National Renewable Energy Laboratory conducted a project to improve the ability of potential technology adopters to evaluate TES technologies. Major project outcomes included: development of an evaluation framework to describe key metrics, methodologies, and issues to consider when assessing the performance of TES systems integrated with packaged AC; application of multiple concepts from the evaluation framework to analyze performance data from four demonstration sites; and production of a new simulation capability that enables modeling of TES integrated with packaged AC in EnergyPlus. This report includes the evaluation framework and analysis results from the project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Application of Framework for Integrating Safety, Security and Safeguards (3Ss) into the Design Of Used Nuclear Fuel Storage Facility

Department of Energy’s Office of Nuclear Energy, Fuel Cycle Research and Development develops options to the current commercial fuel cycle management strategy to enable the safe, secure, economic, and sustainable expansion of nuclear energy while minimizing proliferation risks by conducting research and development focused on used nuclear fuel recycling and waste management to meet U.S. needs. Used nuclear fuel is currently stored onsite in either wet pools or in dry storage systems, with disposal envisioned in interim storage facility and, ultimately, in a deep-mined geologic repository. The safe management and disposition of used nuclear fuel and/or nuclear waste is a fundamental aspect of any nuclear fuel cycle. Integrating safety, security, and safeguards (3Ss) fully in the early stages of the design process for a new nuclear facility has the potential to effectively minimize safety, proliferation, and security risks. The 3Ss integration framework could become the new national and international norm and the standard process for designing future nuclear facilities. The purpose of this report is to develop a framework for integrating the safety, security and safeguards concept into the design of Used Nuclear Fuel Storage Facility (UNFSF). The primary focus is on integration of safeguards and security into the UNFSF based on the existing Nuclear Regulatory Commission (NRC) approach to addressing the safety/security interface (10 CFR 73.58 and Regulatory Guide 5.73) for nuclear power plants. The methodology used for adaptation of the NRC safety/security interface will be used as the basis for development of the safeguards /security interface and later will be used as the basis for development of safety and safeguards interface. Then this will complete the integration cycle of safety, security, and safeguards. The overall methodology for integration of 3Ss will be proposed, but only the integration of safeguards and security will be applied to the design of the UNFSF. The framework for integration of safeguards and security into the UNFSF will include 1) identification of applicable regulatory requirements, 2) selection of a common system that share dual safeguard and security functions, 3) development of functional design criteria and design requirements for the selected system, 4) identification and integration of the dual safeguards and security design requirements, and 5) assessment of the integration and potential benefit.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Collaborative development of the EPICS Qt framework Phase I Final Report

At Lyncean, a private company spun-off from technology developed at the SLAC National Lab, we have been using EPICS for over a decade. EPICS is ubiquitous on our flagship product – the Compact Light Source. EPICS is not only used to control our laser and accelerator systems, but also to control our x-ray beamlines. The goal of this SBIR is for Lyncean Technologies to spearhead a worldwide collaborative effort for the development of control system tools for EPICS using the Qt framework, a C++-based coding environment that could serve as a competitive alternative to the Java-based Control System Studio (CSS). This grant's Phase I, not unlike a feasibility study, is designed for planning and scoping the preparatory work needed for Phase II or other funding opportunities. The three main objectives of this Phase I are (1) to become better acquainted with the existing EPICS Qt software and Qt framework in order to evaluate the best options for ongoing development, (2) to demonstrate that our engineers can lead the EPICS community and jump-start the Qt collaboration, and (3) to identify a scope for our future work with solicited feedback from the EPICS community. This Phase I report includes key technical findings. It clarifies the differences between the two apparently-competing EPICS Qt implementations, caQtDM and the QE Framework; it explains how to create python-bindings, and compares Qt graphical libraries. But this report is also a personal story that narrates the birth of a collaboration. Starting a collaboration is not the work of a single individual, but the work of many. Therefore this report is also an attempt to publicly give credit to many who supported the effort. The main take-away from this grant is the successful birth of an EPICS Qt collaboration, seeded with existing software from the PSI and the Australian Synchrotron. But a lot more needs to be done for the collaboration founders' vision to be realized, and for the collaboration to reach its full potential. To help define the scope of future work, a useful approach we have identified is user experience design (UXD) and is discussed herein.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Controlling Methane Emissions in the Natural Gas Sector. A Review of Federal and State Regulatory Frameworks Governing Production, Gathering, Processing, Transmission, and Distribution

This report provides an overview of the regulatory frameworks governing natural gas supply chain infrastructure siting, construction, operation, and maintenance. Information was drawn from a number of sources, including published analyses, government reports, in addition to relevant statutes, court decisions and regulatory language, as needed. The scope includes all onshore facilities that contribute to methane emissions from the natural gas sector, focusing on three areas of state and federal regulations: (1) natural gas pipeline infrastructure siting and transportation service (including gathering, transmission, and distribution pipelines), (2) natural gas pipeline safety, and (3) air emissions associated with the natural gas supply chain. In addition, the report identifies the incentives under current regulatory frameworks to invest in measures to reduce leakage, as well as the barriers facing investment in infrastructure improvement to reduce leakage. Policy recommendations regarding how federal or state authorities could regulate methane emissions are not provided; rather, existing frameworks are identified and some of the options for modifying existing regulations or adopting new regulations to reduce methane leakage are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

An Information Theoretic Framework and Self-organizing Agent- based Sensor Network Architecture for Power Plant Condition Monitoring

A central goal of the work was to enable both the extraction of all relevant information from sensor data, and the application of information gained from appropriate processing and fusion at the system level to operational control and decision-making at various levels of the control hierarchy through: 1. Exploiting the deep connection between information theory and the thermodynamic formalism, 2. Deployment using distributed intelligent agents with testing and validation in a hardware-in-the loop simulation environment. Enterprise architectures are the organizing logic for key business processes and IT infrastructure and, while the generality of current definitions provides sufficient flexibility, the current architecture frameworks do not inherently provide the appropriate structure. Of particular concern is that existing architecture frameworks often do not make a distinction between ``data'' and ``information.'' This work defines an enterprise architecture for health and condition monitoring of power plant equipment and further provides the appropriate foundation for addressing shortcomings in current architecture definition frameworks through the discovery of the information connectivity between the elements of a power generation plant. That is, to identify the correlative structure between available observations streams using informational measures. The principle focus here is on the implementation and testing of an emergent, agent-based, algorithm based on the foraging behavior of ants for eliciting this structure and on measures for characterizing differences between communication topologies. The elicitation algorithms are applied to data streams produced by a detailed numerical simulation of Alstom’s 1000 MW ultra-super-critical boiler and steam plant. The elicitation algorithm and topology characterization can be based on different informational metrics for detecting connectivity, e.g. mutual information and linear correlation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2016

Characterizing the Benefits of Seismic Isolation for Nuclear Structures: A Framework for Risk-Based Decision Making

This report provides a framework for assessing the benefits of seismic isolation and exercises the framework on a Generic Department of Energy Nuclear Facility (GDNF). These benefits are (1) reduction in the risk of unacceptable seismic performance and a dramatic reduction in the probability of unacceptable performance at beyond-design basis shaking, and (2) a reduction in capital cost at sites with moderate to high seismic hazard. The framework includes probabilistic risk assessment and estimates of overnight capital cost for the GDNF.

42 ENGINEERING↗
DOE OSTI2016

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Regulatory Risk Reduction for Advanced Reactor Technologies: FY 2017 Framework Modernization Proposals and Status

The regulatory framework governing the licensing of commercial nuclear power plants in the U.S. developed over recent decades with a strong emphasis towards assessing large light water reactor (LWR) safety. However, recent shifts in energy market needs and priorities has brought new and different types of nuclear technologies into consideration for applications that include but are not limited to electric power generation. In order to realize the benefits in efficiency, reliability and safety that advanced (non-LWR) can potentially offer, efforts are needed to modernize the existing regulatory framework to make technical licensing requirements more compatible with radically new nuclear technologies. To serve the needs of the energy market, this update should be performed on a schedule conducive to deployments projected to begin as early as 2025. Beginning in 2016, an initiative was launched to amend the U.S. nuclear power reactor licensing framework by making the technical requirements contained therein more generically compatible with non LWR technology. The Licensing Modernization Project (LMP) was established as an industry-led team of subject matter experts managed by Southern Company Services and supported through a cost sharing arrangement with the U.S. Department of Energy (DOE). Technical and programmatic coordination for the effort was also provided by the Nuclear Energy Institute (NEI), the Licensing Department of the Advanced Reactor Technologies (ART) Program located at the Idaho National Laboratory (INL), and others.

42 ENGINEERING↗