Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “analytics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Smart Manufacturing Technologies and Data Analytics for Improving Energy Efficiency in Industrial Energy Systems

Smart manufacturing and advanced data analytics can help the manufacturing sector unlock energy efficiency from the equipment level to the entire manufacturing facility and the whole supply chain. These technologies can make manufacturing industries more competitive, with intelligent communication systems, real-time energy savings, and increased energy productivity. Smart manufacturing can give all employees in an organization the actionable information they need, when they need it, so that each person can contribute to the optimal operation of the corporation through informed, data-driven decision making. This paper examines smart technologies and data analytics approaches for improving energy efficiency and reducing energy costs in process-supporting energy systems. It dives into energy-saving improvement opportunities through smart manufacturing technologies and sophisticated data collection and analysis. The energy systems covered in this paper include those with motors and drives, fans, pumps, air compressors, steam, and process heating.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Can You Verifi This? Studying Uncertainty and Decision-Making About Misinformation using Visual Analytics

We describe a novel study of decision-making processes around misinformation on social media. Using a custom-built visual analytic system, we presented users with news content from social media accounts from a variety of news outlets, including outlets engaged in distributing misinformation. We conducted controlled experiments to study decision-making regarding the veracity of these news outlets and tested the role of confirmation bias (the tendency to ignore contradicting information) and uncertainty of information on human decision-making processes. Our findings reveal that the presence of conflicting information, presented to users in the form of cues, impacts the ability to judge the veracity of news in systematic ways. We also find that instructing participants even to explicitly disconfirm given hypotheses does not significantly impact their decision-making regarding misinformation when compared to a control condition. Our findings have the potential to inform the design of visual analytics systems so that they may be used to mitigate the effects of cognitive biases and stymie the spread of misinformation on social media.

misinformation, decision making, social media, vis↗
DOE OSTI2020

Metrics and Analytical Frameworks for Valuing Energy Efficiency and Distributed Energy Resources in the Built Environment: Preprint

This paper summarizes efforts to develop new—and enhance existing—analytical frameworks and metrics to quantify the value that grid-interactive efficient homes with solar (GEB-solar homes) can provide. Industry is working to characterize and understand these capabilities and benefits, but existing analytical frameworks for evaluating energy efficiency (EE) are often siloed from those that evaluate distributed energy resources (DERs). Five metrics were adapted from an extensive literature review and applied to case studies of a modeled home in Riverside, California: ramp up/down, cover factor demand/supply, and curtailable load. Eight different technology scenarios were analyzed using a more tightly connected suite of building-to-grid models (BEopt, REopt, ReEDS, and PLEXOS). Additionally, an initial version of the Cambium tool was developed, characterizing the marginal prices and emissions from NREL’s 2018 Standard Scenarios. These grid costs were extended to a time-varying proxy retail rate and applied as part of a new grid alignment metric. In the results, a more integrated combination of GEB-solar technologies led to a higher cover factor demand—the percentage of gross home load covered by on-site solar—however, a benchmark was required to determine what range of cover factor was “best” for given grid conditions. To that end, a grid alignment cost metric was applied to the case study scenarios. The average cost to serve the net load of the home decreased from a median of ~$0.24/kWh to ~$0.10/kWh when the most integrated technology scenario was optimized towards the grid pricing proxy versus the time-of-use (TOU) rate.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Status on Development of Graphite Analytical Tool (GAT)

The DOE-ART Graphite R&D program has been generating significant amounts of irradiated and unirradiated graphite data since 2006 when the program was part of the DOE NGNP (Next Generation Nuclear Plant) Project. This data includes critical irradiation creep and irradiated material property changes from the Advanced Graphite Creep (AGR) experiment as well as significant amounts of data on unirradiated material property values on several current nuclear graphite grades (Baseline program). Previously, Idaho National Laboratory has developed an internal analysis tool to assist with analysis of the unirradiated and irradiated data. The Graphite Analytical Tool (GAT) is intended to provide easy access to the graphite data in the form of comparing unirradiated and irradiated material property changes, comparison of material property differences between various nuclear graphite grades, and illustrate trends within the irradiated and unirradiated data generated within the DOE-ART Graphite R&D program. This report summarizes the progress to-date on the development of this analytical tool.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Analytic Sensitivity Coefficients for Bethe's Solution of the Neutron Slowing Down Equation

Neutron slowing down theory is used to derive expressions for the sensitivity coefficients of the neutron collision density in a hydrogenous infinite medium with respect to the fixed source, scattering probability, and macroscopic nuclear cross sections. Analytic expressions for Bethe’s solution of the neutron slowing down equation are derived for the constant cross section approximation with a point, uniform, and gamma lethargy spectrum. Analytic expressions for the corresponding sensitivity coefficients are derived and used to verify Monte Carlo neutron transport calculations.

Analytic Benchmark↗
DOE OSTI2025

INTEGRATION OF DATA ANALYTICS WITH SYSTEM HEALTH PROGRAMS

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry developed and regulatory programs. However, these programs have proven to be labor intensive and expensive. There is an opportunity to significantly enhance the collection, analysis, and use of this information to provide more cost-effective plant operation. Additionally, there is an acute industry need to leverage advanced technology to reduce costs and improve operational effectiveness. The goal of this paper is to provide effective and efficient analytical methods and tools to support risk-informed decisions for the equipment reliability and asset management programs at nuclear power plants. This is accomplished by creating a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). Here we are supporting typical system engineer decisions regarding maintenance activity scheduling and component ageing management. This is performed in a risk-informed context where herein the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow. A challenge is that the structure of this workflow strongly depends on the decision that needs to be made, the type of data available, and the constraints that need to be considered. Current methods are designed to provide specific answers to specific problems; however, these methods might prove to be inadequate even when problem settings slightly change (e.g., different types of requirements, additional dependencies between system reliability and economics). We tackled this challenge by designing framework in a flexible and modular fashion such that the user can assemble and customize his/her own workflow that integrates SSC economic lifecycle models (e.g., maintenance and replacement costs), system reliability models, and optimization methods.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Large Ensemble Analytic Framework for Consequence-Driven Discovery of Climate Change Scenarios

An analytic scenario generation framework is developed based on the idea that the same climate outcome can result from very different socioeconomic and policy drivers. The framework builds on the Scenario Matrix Framework’s abstraction of “challenges to mitigation” and “challenges to adaptation” to facilitate the flexible discovery of diverse and consequential scenarios. We combine visual and statistical techniques for interrogating a large factorial data set of 33,750 scenarios generated using the Global Change Assessment Model. We demonstrate how the analytic framework can aid in identifying which scenario assumptions are most tied to user-specified measures for policy relevant outcomes of interest, specifically for our example high or low mitigation costs. We show that the current approach for selecting reference scenarios can miss policy relevant scenario narratives that often emerge as hybrids of optimistic and pessimistic scenario assumptions. We also show that the same scenario assumption can be associated with both high and low mitigation costs depending on the climate outcome of interest and the mitigation policy context. In the illustrative example, we show how agricultural productivity, population growth, and economic growth are most predictive of the level of mitigation costs. Formulating policy relevant scenarios of deeply and broadly uncertain futures benefits from large ensemble-based exploration of quantitative measures of consequences. To this end, we have contributed a large database of climate change futures that can support “bottom-up” scenario generation techniques that capture a broader array of consequences than those that emerge from limited sampling of a few reference scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Revisiting the Fundamental Analytical Solutions of Heat and Mass Transfer: The Kernel of Multirate and Multidimensional Diffusion

There are two types of analytical solutions of temperature/concentration in and heat/mass transfer through boundaries of regularly shaped 1D, 2D, and 3D blocks. These infinite-series solutions with either error functions or exponentials exhibit highly irregular but complementary convergence at different dimensionless times, t d0 . In this paper, approximate solutions were developed by combining the error-function-series solutions for early times and the exponential-series solutions for late times and by using time partitioning at the switchover time, t d0 . The combined solutions contain either the leading term of both series for normal-accuracy approximations (with less than 0.003 relative error) or the first two terms for high-accuracy approximations (with less than 10-7 relative error) for 1D isotropic (spheres, cylinders, slabs) and 2D/3D rectangular blocks (squares, cubes, rectangles, and rectangular parallelepipeds). This rapid and uniform convergence for rectangular blocks was achieved by employing the same time partitioning with individual dimensionless times for different directions and the product of their combined 1D slab solutions. The switchover dimensionless time was determined to minimize the maximum approximation errors. Furthermore, the analytical solutions of first-order heat/mass flux for 2D/3D rectangular blocks were derived for normal-accuracy approximations. These flux equations contain the early-time solution with a three-term polynomial in √td and the late-time solution with the limited-term exponentials for rectangular blocks. The heat/mass flux equations and the combined temperature/concentration solutions form the ultimate kernel for fast simulations of multirate and multidimensional heat/mass transfer in porous/fractured media with millions of low-permeability blocks of varying shapes and sizes.

42 ENGINEERING↗
DOE OSTI2015

Electron Tomography: A Three-Dimensional Analytic Tool for Hard and Soft Materials Research

Three-dimensional (3D) structural analysis is essential to understand the relationship between the structure and function of an object. Many analytical techniques, such as X-ray diffraction, neutron spectroscopy, and electron microscopy imaging, are used to provide structural information. Transmission electron microscopy (TEM), one of the most popular analytic tools, has been widely used for structural analysis in both physical and biological sciences for many decades, in which 3D objects are projected into two-dimensional (2D) images. In many cases, 2D-projection images are insufficient to understand the relationship between the 3D structure and the function of nanoscale objects. Electron tomography (ET) is a technique that retrieves 3D structural information from a tilt series of 2D projections, and is gradually becoming a mature technology with sub-nanometer resolution. Distinct methods to overcome sample-based limitations have been separately developed in both physical and biological science, although they share some basic concepts of ET. Here, this review discusses the common basis for 3D characterization, and specifies difficulties and solutions regarding both hard and soft materials research. It is hoped that novel solutions based on current state-of-the-art techniques for advanced applications in hybrid matter systems can be motivated. Electron tomography produces quantitative 3D reconstructions for biological and physical sciences from sets of 2D projections acquired at different tilting angles in a transmission electron microscope. Finally, state-of-the-art techniques capable of producing 3D representations such as Pt-Pd core-shell nanoparticles and IgG1 antibody molecules are reviewed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A graph signal processing‐based multiple model Kalman filter ( GSP‐MMKF ) tool for predictive analytics: An air separation unit process application

Abstract The industrial Air Separations Unit (ASU) is a complicated and tightly operated process. The use of dynamic process analytics is also a key element of safe and economic operation of these processes, with increasing focus on predictive analytics to take preemptive actions. With the availability of real‐time data from hundreds of sensors, the data analysis process should also consider the topology of the data, as seen in sensor networks. In this paper, a novel tool is presented that considers the complex connectivity patterns in the sensor network and uses local adaptive disturbance estimations to predict global network‐scale trends. The paper introduces the emerging field of Graph Signal Processing (GSP) and presents a rigorous derivation of the tool starting from the extraction of the sensor‐network (in a graph theoretical sense) from the data. This network, which is in the form of a matrix, is then used to derive a Kalman‐filter type of state‐space model driven by input disturbances. Multiple disturbance models (e.g., step, ramp, periodic) are included to allow the model to have different kinds of disturbance propagation. Each graph node (representing the sensors used) dynamically adapts to the most recent detected disturbance individually. These estimated disturbances are propagated to the global network using the graph. Modifications to ensure stability are also discussed. The fidelity of the tool is tested on certain downtime events and the paper concludes by discussing the advantages of the method and planned future improvements.

Ghosh, Sambit↗
DOE OSTI2022

Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing

The 2021 Smoky Mountains Computational Sciences and Engineering Conference enlists scientists from across Oak Ridge National Laboratory (ORNL) and industry to be data sponsors and help create data analytics and edge computing challenges for eminent datasets in a variety of scientific domains. This work describes the significance of each of the eight datasets and their associated challenge questions. The challenge questions for each dataset were required to cover multiple difficulty levels. An international call for participation was sent to students, asking them to form teams of up to six people and apply novel data analytics and edge computing methods to solve these challenges.

Devineni, Pravallika↗
DOE OSTI2024

Challenges for monitoring and data analytics in a leadership public data repository

The availability and disposition of data has assumed increasing importance in large-scale computational science. Data repositories are evolving to meet new classes of requirements: compliance with government access guidelines, support for reproducibility of experimental results, and long-term availability of data products. The Constellation public data repository at the Oak Ridge Leadership Computing Facility faces these issues while being situated in one of the most productive data centers in the world. While monitoring and operational data analysis are ingrained in the operation of the OLCF’s large-scale high performance computing platforms, data repositories do not have this history of support. Problems faced by Constellation range from data size (over 7 petabytes in current holdings) to analytic complexity (detailed curation is both absolutely necessary for many data sets and absolutely impossible for humans to accomplish in any practical manner) to deployment environment (OLCF storage resources are oriented toward the needs of the compute platforms). In this paper we describe some of the challenges for collecting monitoring and analytic data from a leadership public data repository. We also discuss various strategies we are pursuing in order to address these challenges, from manual data collection to plans for introducing machine learning-based curatorial techniques.

Widener, Patrick [ORNL] (ORCID:0000000258820816)↗
DOE OSTI2019

Gravitational production of super-Hubble-mass particles: an analytic approach

Through a mechanism similar to perturbative particle scattering, particles of mass m χ larger than the Hubble expansion rate H inf during inflation can be gravitationally produced at the end of inflation without the exponential suppression powers of exp(-m χ /H inf ). Here we develop an analytic formalism for computing particle production for such massive particles. We apply our formalism to specific models that have been previously been studied only numerically, and we find that our analytical approximations reproduce those numerical estimates well.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Exact quantization and analytic continuation

In this paper we give a streamlined derivation of the exact quantization condition (EQC) on the quantum periods of the Schrödinger problem in one dimension with a general polynomial potential, based on Wronskian relations. We further generalize the EQC to potentials with a regular singularity, describing spherical symmetric quantum mechanical systems in a given angular momentum sector. We show that the thermodynamic Bethe ansatz (TBA) equations that govern the quantum periods undergo nontrivial monodromies as the angular momentum is analytically continued between integer values in the complex plane. The TBA equations together with the EQC are checked numerically against Hamiltonian truncation at real angular momenta and couplings, and are used to explore the analytic continuation of the spectrum on the complex angular momentum plane in examples.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Bounding the Higgs width at the LHC using full analytic results for $gg → e^- e^+ \mu^- \mu^+$

We revisit the hadronic production of the four-lepton final state, e – e + μ – μ + , through the fusion of initial state gluons. This process is mediated by loops of quarks and we provide first full analytic results for helicity amplitudes that account for both the effects of the quark mass in the loop and off-shell vector bosons. The analytic results have been implemented in the Monte Carlo program MCFM and are both fast, and numerically stable in the region of low Z transverse momentum. We use our results to study the interference between Higgs-mediated and continuum production of four-lepton final states, which is necessary in order to obtain accurate theoretical predictions outside the Higgs resonance region. We have confirmed and extended a recent analysis of Caola and Melnikov that proposes to use a measurement of the off-shell region to constrain the total width of the Higgs boson. Using a simple cut-and-count method, existing LHC data should bound the width at the level of 25-45 times the Standard Model expectation. We investigate the power of using a matrix element method to construct a kinematic discriminant to sharpen the constraint. Furthermore, in our analysis the bound on the Higgs width is improved by a factor of about 1.6 using a simple cut on the MEM discriminant, compared to an invariant mass cut μ 4l > 300 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Analytic techniques for solving the transport equations in electroweak baryogenesis

We develop an efficient method for solving transport equations, particularly in the context of electroweak baryogenesis. It provides fully-analytical results under mild approximations and can also test semi-analytical results, which are applicable in more general cases. Key elements of our method include the reduction of the second-order differential equations to first order, representing the set of coupled equations as a block matrix of the particle densities and their derivatives, identification of zero modes, and block decomposition of the matrix. We apply our method to calculate the baryon asymmetry of the Universe (BAU) in a Standard Model effective field theory framework of complex Yukawa couplings to determine the sensitivity of the resulting BAU to modifications of various model parameters and rates, and to estimate the effect of the commonly-used thin-wall approximation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

More analytic bootstrap: nonperturbative effects and fermions

We develop the analytic bootstrap in several directions. First, we discuss the appearance of nonperturbative effects in the Lorentzian inversion formula, which are exponentially suppressed at large spin but important at finite spin. We show that these effects are important for precision applications of the analytic bootstrap in the context of the 3d Ising and O(2) models. In the former they allow us to reproduce the spin-2 stress tensor with error at the 10 -5 level while in the latter requiring that we reproduce the stress tensor allows us to predict the coupling to the leading charge-2 operator. We also extend perturbative calculations in the lightcone bootstrap to fermion 4-point functions in 3d, predicting the leading and subleading asymptotic behavior for the double-twist operators built out of two fermions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Analytic calculation of 1-jettiness in DIS at O (α s )

We present an analytic O(α s ) calculation of cross sections in deep inelastic scattering (DIS) dependent on an event shape, 1-jettiness, that probes final states with one jet plus initial state radiation. This is the first entirely analytic calculation for a DIS event shape cross section at this order. We present results for the differential and cumulative 1-jettiness cross sections, and express both in terms of structure functions dependent not only on the usual DIS variables x, Q 2 but also on the 1-jettiness τ. Combined with previous results for log resummation, predictions are obtained over the entire range of the 1-jettiness distribution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗