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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantifying the Impact of Transportation on Climate - Energy Analytics Dashboard: Preprint

The investment decisions within the nation's transportation sector have traditionally been prioritized and measured against safety and travel efficiency goals. Increasingly, federal, state, and local policies are requiring consideration of energy use and emissions in the design of our transportation infrastructure. Yet the processes, analytics, and knowledge to include these new metrics into transportation decisions are lacking. Although targeted studies and before and after analysis are performed from time to time, no comprehensive real-time monitoring systems provide energy and emissions to the same level as congestion and safety. To address this gap, this paper developed and demonstrated the Transportation Energy Analytics Dashboard, or TEAD, to raise awareness of the energy and emission impacts to the same level of observability as that of safety and mobility concerns.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2023

Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance, Version 2.0

The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112) EV-ChART will provide a streamlined data submission process and an integrated set of analytic tools, connect to other data sources, and empower data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112. The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2023

Assessing the Performance of a Circular Economy for Wind Energy Technologies: A Summary of Three Analytical Tools

A circular economy emphasizes the efficient use of all resources and presents opportunities for addressing series of economic and environmental objectives at local, regional, and national levels. Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. As a result, it is important to evaluate the performance and tradeoffs associated with circular economy transitions. This poster summaries three previously published analytical tools that were used to assess the performance of developing a circular economy for wind energy technologies: the Renewable Energy Materials Properties Database (REMPD), a circular economy agent-based model for wind blades (CE Wind ABM), and the Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework. The REMPD is a comprehensive database of materials used in wind and solar plants, including material quantities and physical materials availability. The CE Wind ABM allows us to understand how wind stakeholders' end-of-life behaviors influence wind blade circularity and evaluate the impact of regional variables (e.g., logistics and transportation). And, the CELAVI framework is a modular framework that can be used to evaluate the impacts associated with circular economy transitions. These three analytical tools have been applied to evaluate circular economy transitions for wind energy technologies and they could be expanded to other technologies and products.

agent-based modeling↗
DOE OSTI2023

Process for ultra-sensitive quantification of target analytes in complex biological systems

Antibody-free processes are disclosed that provide accurate quantification of a wide variety of low-abundance target analytes in complex samples. The processes can employ high-pressure, high-resolution chromatographic separations for analyte enrichment. Intelligent selection of target fractions may be performed via on-line Selected Reaction Monitoring (SRM) or off-line rapid screening of internal standards. Quantification may be performed on individual or multiplexed fractions. Applications include analyses of, e.g., very low abundance proteins or candidate biomarkers in plasma, cell, or tissue samples without the need for affinity-specific reagents.

Shi, Tujin↗
DOE OSTI2023

Characterizing Reactor Operations from Realistic Simulated Environmental Samples: Combining High-Performance Computing and Data Analytics

Environmental sampling is a common technique employed by inspectors and facility operators in nuclear safeguards, proliferation detection, and process monitoring contexts. Interpreting measurements performed on samples or collections of samples and ensuring the information extracted is accurate and precise is difficult. To date, these analyses have relied on simulated data to enable systematic studies; however, these models are inherently limited by the fidelity of the models and the implicit spatial averaging of isotopic composition or other signatures of interest. To advance this capability, we have refined the spatial discretization and expanded the range of physics in the simulation codes we use to perform reactor simulations and depletion calculations. This allows us to generate data that are more representative of real environmental samples, especially for the length scale of the isotopic composition and associated variation. Accordingly, these new data allow a more realistic assessment of traditional and new data analytic analysis methods. Here we present motivation for developing reactor simulations using high-performance computing methods and resources, impacts of these new simulations on our assessment of data analysis and interpretation methods, and initial results of developing and systematically testing data analytic methods designed to overcome the challenges expected of real-world samples. We also quantify the performance of these analyses using defensible statistical methods.

Dayman, Ken J.↗
DOE OSTI2017

Coupling Big Data Analytics and Reactive Transport Modeling for Cost-effective Groundwater Monitoring - 17163

This study presents an innovative approach for sustainable and cost-effective groundwater monitoring. This approach takes advantage of recent advances in various technologies: (1) in situ autonomous sensors, (2) big data analytics, and (3) parallel high-performance computing for flow and reactive transport modeling. In situ sensors are used to periodically measure the key variables (such as pH, redox potential, electrical conductivity, and groundwater level), which control contaminant mobility and the plume spatial and temporal distribution. Based on a limited number of groundwater sampling, the data analytics methods-data mining and machine learning-allow us to identify and quantify the correlations between the in situ-measured variables and contaminant concentrations, and also to detect significant changes associated with the plume mobility. In addition, a state-of-the-art parallel numerical flow and reactive transport simulator Amanzi, and uncertainty quantification software Agni are used to provide an improved physical and mechanistic understanding of the contaminated groundwater system behavior, and to predict the long-term plume distribution for optimizing and adapting the monitoring strategy. Amanzi and Agni were developed as part of the Advanced Simulation Capability for Environmental Management (ASCEM) program of the DOE Office of Environmental Management. Such modeling is critical, particularly, for assessing the impact of climate change and associated hydrological shifts. The developed approach is expected to significantly reduce the groundwater sampling frequency and associated cost. In addition, the real-time information on plume mobility serves as an early warning system, improving the resiliency of contaminated or potentially contaminated sites. We demonstrate this approach using as an example the Savannah River Site (SRS) F-Area, where groundwater is contaminated by various radionuclides, including uranium, tritium and technetium. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Knowledge management information tool analytics with distributed database engine - 15737

The D and D KM-IT is a web-based knowledge management information tool custom built for the deactivation and decommissioning (D and D) user community. The system allows interested users to post information which goes through a custom work flow. To better improve the performance and user experience, the analysis of server logs is being conducted using MongoDB. MongoDB is a document database that provides high performance, high availability, and easy scalability. Objectives: - Feasibility study of Distributed Database Engine, MongoDB for web analytics; - Analyze server logs to evaluate D and D KM-IT module usage; - Generate useful information from the analysis. Method: - The server logs were loaded and stored in MongoDB for analysis; - Analysis and visualization was performed using NodeJS and Java Script library. Results: - It was possible to store log files in MongoDB; - Log files with different time stamps and groups from different servers can be aggregated; - Queries can be written to extract meaningful information from aggregated log files (e.g. users from different countries/organizations). Conclusions: - MongoDB is useful for server log analytics as the analyst can immediately access, analyze, and visualize MongoDB data based on the requirements; - The information can be extracted to develop custom reports; - Optimized queries can be run for fast data access. Path forward: - Custom queries need to be developed to extract information leading to improved user information.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Qualification of Numerical and Semi-Analytical Modeling Codes for Thermal Design of HLW Repository - 18455

Disposal in a geological repository is a viable option for safely isolating high-level radioactive waste. Thermal processes induced by decay heat from the radioactive waste may impact the integrity of the engineered barrier system, and may lead to fluid flow and transport; and the associated migration of radionuclides. This study looks at an analysis of thermal conduction for the emplacement of high-level waste in a repository located in bedded salt. The simulations used analytical and numerical methods to study conductive heat transport in a repository. This study concentrated on heat flow in a central waste package with contributions from adjacent waste packages and drifts. Of particular importance to this work is comparison of predictions of peak temperature at the drift wall and at the waste package surface using different solution methods. Simulation results of analytical and numerical modeling methods are compared. The results show that predictions of the codes were comparable under identical initial and boundary conditions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Providing plant data analytics through a seamless digital environment - 211

As technology continues to evolve and become more integrated into a worker's daily routine in the commercial nuclear power industry the need for easy access to data becomes a priority. Not only does the need for data increase but the amount of data collected increases. In most cases the data is collected and stored in various software applications, many of which are legacy systems, which do not offer any other option to access the data except through the application's user interface. Furthermore the data get grouped in 'silos' according to work function and not necessarily by subject. Hence, in order to access all the information needed for a particular task or analysis one may have to access multiple applications to gather all the data needed. The industry and the research community have identified the need for a digital architecture and more importantly the need for a Seamless Digital Environment (SDE). An SDE provides a means to access multiple applications, gather the data points needed, conduct the analysis requested, and present the result to the user with minimal or no effort by the user. The study researches the potential approaches to building an analytics solution for equipment reliability, on a small scale, focusing on either a single piece of equipment or a single system. The analytics solution will consist of a data integration layer, predictive and machine learning layer and the user interface layer that will display the output of the analysis in a straight forward, easy to consume manner. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Industry analytics to optimize time based maintenance for I and C components - 363

Using Industry Analytics to optimize time based maintenance for I and C components allows a nuclear site to increase cost efficiency without impacting equipment reliability. Reductions in frequency or deletions for non-value based Preventive Maintenance (PM) improves cost efficiency by decreasing man-hours, parts costs, and planning costs of that PM; while maintenance performed too frequently can induce maintenance related failures. Benchmarking Industry PM Performance and Equipment Failure data allows sites to efficiently optimize time based maintenance frequencies. Equipment Failure history identifies gaps in maintenance frequencies as well maintenance-induced failures. Overlapping the PM frequency from a site with Industry PM Performance identifies opportunities to justify cost savings by reducing the PM frequency. The opportunities are then validated by the site's living PM program to ensure that the site can support the extension. This paper will discuss an Industry analytical technique used for maintenance frequency reductions. The major aspects evaluated under the technique are validation of the Industry data, review of the component's history and comparison of additional information. Industry data from 180 sites is used as a benchmark to identify opportunities for PM frequency extension on like-for-like components based on manufacturer/model and application. The component history composed of preventive maintenance feedback history and corrective maintenance history is reviewed to determine if the frequency can be extended without adversely affecting equipment reliability. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Analytical calculation for the solid angle subtended at an arbitrarily positioned point source by an ellipse - Paper 38

The geometrical solid angle can be used to calibrate radiation detectors or to determine the activity of radioactive sources. In the present work, we introduce a direct analytical method for calculating the solid angle subtended at an arbitrarily positioned point source by a closed contour (ellipse). The validity of the derived analytical expressions was successfully confirmed by the comparison with some published data (Numerical Method). Direct mathematical expressions to calculate the geometrical solid angle subtended by an elliptical disk detector with respect to arbitrarily positioned radiating point sources have been derived. The agreement between the calculated and the published solid angle values is excellent; the discrepancies were (0.0%). This means that the present approach is efficient and sufficiently powerful to evaluate the geometrical efficiency of the elliptical disk detectors. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Advanced Tritium Process Analytics and Optimization via a Digital Twin, SRNL-TR-2023-00550

Improving the process knowledge and understanding of TCAP can be achieved by incorporating advanced tools. This project addresses “Advanced analytics for modeling, forecasting, & optimization of the tritium refinement process” and is being applied to the TCAP process. The value of digitization and advanced analytics for TCAP data are tracking of gas mixtures & inventories is presently a manual effort that is rather cumbersome. Incorporating some automation into the data capture will reduce errors and storing data in an accessible database that can be used for tracking as well as process improvements. In addition, the database approach will enable longer term history to be maintained rather than the current practice of deleting data after six months. The digitized and automated data will allow for models to be developed for the process and will enable the forecasting and optimization.

Korinko, Paul S.↗
DOE OSTI2024

Analyticity and the Unruh effect: a study of local modular flow

The Unruh effect can be formulated as the statement that the Minkowski vacuum in a Rindler wedge has a boost as its modular flow. In recent years, other examples of states with geometrically local modular flow have played important roles in understanding energy and entropy in quantum field theory and quantum gravity. Here I initiate a general study of the settings in which geometric modular flow can arise, showing (i) that any geometric modular flow must be a conformal symmetry of the background spacetime, and (ii) that in a well behaved class of “weakly analytic” states, geometric modular flow must be future-directed. I further argue that if a geometric transformation is conformal but not isometric, then it can only be realized as modular flow in a conformal field theory. Finally, I discuss a few settings in which converse results can be shown — i.e., settings in which a state can be constructed whose modular flow reproduces a given vector field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Data Analytics for Catalysis Predictions: Are We Ready Yet?

Catalysis informatics has received tremendous attention in recent years as a tool to design catalysts and discover unique descriptors that capture the relationships between chemical properties and catalytic performance. One of the stop-gaps in understanding catalytic effects, which is often ignored and limits the deployment of data science tools, relates to the lack of uniform data. The catalytic cleavage of C–X (X= H, C, N, and O) bonds is relevant to many fundamental catalytic processes. In this Perspective, we performed data analytics on four groups of C–X cleavage reactions that are common in production, upcycling, or reactive separation: the C–C cleavage in cyclopropyl alcohol, the C–H cleavage in hydroacylation reactions, the C–O cleavage in β-O-4 linkages, and the C–N cleavage in amides, using experimental data collected from the literature to understand their underlying correlations. Experimental variables of high impact are identified for each reaction by dimensionality reduction methods. We highlight the urgent need for experimental data sets that include full details on the reaction conditions, such as reagent concentration, reaction temperature, or time in machine-readable forms. We discuss the potential improvement of the data of these reactions and promising approaches such as autonomous experiments to fill the gaps in unbiased experimental data. Finally, we also address the early stage consideration of separation aspects in the experimental design of efficient catalytic systems for these fundamental examples of chemical reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Inverse patchy colloids with two and three patches. Analytical and numerical study

We propose an analytical solution of the multi-density Ornstein-Zernike equation supplemented by the associative Percus-Yevick closure relations specifically designed to describe the equilibrium properties of the novel class of patchy colloidal particles represented by the inverse patchy colloids with arbitrary number of patches. Using Baxter’s factorization method, we reduce solution of the problem to the solution of one nonlinear algebraic equation for the fraction of the particles with one non-bonded patch. We present closed-form expressions for the structure (structure factor) and thermodynamic (internal energy) properties of the system in terms of this fraction (and parameters of the model). We perform computer simulation studies and compare theoretical and computer simulation predictions for the pair distribution function, internal energy, and number of single and double bonds formed in the system, for two versions of the model, each with two and three patches. We consider the models with formation of the double bonds blocked by the patch-patch repulsion and the models without patch-patch repulsion. In general very good agreement between theoretical and computer simulation results is observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Analytic gradients for relativistic exact-two-component equation-of-motion coupled-cluster singles and doubles method

A first implementation of analytic gradients for spinor-based relativistic equation-of-motion coupled-cluster singles and doubles method using an exact two-component Hamiltonian augmented with atomic mean-field spin–orbit integrals is reported. To demonstrate its applicability, we present calculations of equilibrium structures and harmonic vibrational frequencies for the electronic ground and excited states of the radium mono-amide molecule (RaNH 2 ) and the radium mono-methoxide molecule (RaOCH 3 ). Spin–orbit coupling is shown to quench Jahn–Teller effects in the first excited state of RaOCH 3 , resulting in a C 3v equilibrium structure. Furthermore, the calculations also show that the radium atoms in these molecules serve as efficient optical cycling centers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

The Academic Tree of Howard V. Malmstadt: From Early Scientific Exploration to Modern Analytical Chemistry

Over the last several decades, science has benefited tremendously by the implementation of digital electronic components for analytical instrumentation. A pioneer in this area of scientific inquiry was Howard Malmstadt. Frequently, such revolutions in scientific history can be viewed as a series of discoveries without a great deal of attention as to how mentorship shapes the careers and methodologies of those who made great strides forward for science. Here, this article focuses on the verifiable relationships of those who are connected through the academic tree of Malmstadt and how their experiences and the context of world events influenced their scientific pursuits. Particular attention is dedicated to the development of American chemistry departments and the critical role played by many of the individuals in the tree in this process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗