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At least 1,207 records · Page 67

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Analytical Calculation of the Energy Deposition Spectrum and Average Dose to A Spherical Target By Ion Tracks at All Impact Parameters

Microdosimetry is used to estimate quality factors for risk assessment in radiation protection [1] and to quantify relative biological effectiveness (RBE) for treatment planning of hadron radiation therapy [2]. Radiation physics has shown that energetic ions deposit energy in a complex manner: the track structure. The Local Effect Model (LEM) [3] is often used as an approximation to describe this complex track structure. We have previously calculated an analytical expression for the dose to a spherical target fully located in the penumbra of an ion track using the LEM [4]. In this work, the calculation has been extended to all impact parameters. Furthermore, using these analytical expressions, it was possible to obtain the theoretical energy deposition spectra to a sphere irradiated uniformly.

I Plante↗

NASA NTRSDate not supplied

Analytical Calculation of the Energy Deposition Spectrum and Average Dose to A Spherical Target at All Impact Parameters

Microdosimetry is used to estimate quality factors for risk assessment in radiation protection and to quantify relative biological effectiveness (RBE) for treatment planning of hadron radiation therapy. Radiation physics has shown that energetic ions deposit energy in a complex manner: the track structure. The Local Effect Model (LEM) is often used as an approximation to describe this complex track structure. We have previously calculated an analytical expression for the dose to a spherical target fully located in the penumbra of an ion track using the LEM. In this work, the calculation has been extended to all impact parameters. Furthermore, using these analytical expressions, it was possible to obtain the theoretical energy deposition spectra to a sphere irradiated uniformly.

Ianik Plante↗

NASA NTRSDate not supplied

Analytical Flight Dynamic Model Development for eVTOL Aircraft

This paper presents an analytical flight dynamic model development method for a multi- rotor eVTOL aircraft in hover and transition flight. The method captures the analytical stability and control sensitivities of rotor unsteady aerodynamic loads about a trim solution generated by a rotorcraft aeromechanics comprehensive analysis tool. The rotor aerody- namic forces include circulatory and non-circulatory components to account for unsteady aerodynamics. The circulatory forces are corrected for unsteady aerodynamics using the time-domain approximation of Theodorsen’s function. The integrated flight dynamic model includes the rigid-body aircraft flight dynamics, inflow dynamics, unsteady aerodynamics, and blade pitch and rotor actuator dynamics. Stability analyses shows that the Lift+Cruise aircraft is statically unstable in roll and yaw axes and also dynamically unstable in hover. Closed-loop feedback control is necessary for stable hover flight.

rotorcraft↗

DOE OSTI2013

Deep Sludge Gas Release Event Analytical Evaluation

Long Abstract. Full Text. The purpose of the Deep Sludge Gas Release Event Analytical Evaluation (DSGRE-AE) is to evaluate the postulated hypothesis that a hydrogen GRE may occur in Hanford tanks containing waste sludges at levels greater than previously experienced. There is a need to understand gas retention and release hazards in sludge beds which are 200 -300 inches deep. These sludge beds are deeper than historical Hanford sludge waste beds, and are created when waste is retrieved from older single-shell tanks (SST) and transferred to newer double-shell tanks (DST).Retrieval of waste from SSTs reduces the risk to the environment from leakage or potential leakage of waste into the ground from these tanks. However, the possibility of an energetic event (flammable gas accident) in the retrieval receiver DST is worse than slow leakage. Lines of inquiry, therefore, are (1) can sludge waste be stored safely in deep beds; (2) can gas release events (GRE) be prevented by periodically degassing the sludge (e.g., mixer pump); or (3) does the retrieval strategy need to be altered to limit sludge bed height by retrieving into additional DSTs? The scope of this effort is to provide expert advice on whether or not to move forward with the generation of deep beds of sludge through retrieval of C-Farm tanks. Evaluation of possible mitigation methods (e.g., using mixer pumps to release gas, retrieving into an additional DST) are being evaluated by a second team and are not discussed in this report. While available data and engineering judgment indicate that increased gas retention (retained gas fraction) in DST sludge at depths resulting from the completion of SST 241-C Tank Farm retrievals is not expected and, even if gas releases were to occur, they would be small and local, a positive USQ was declared (Occurrence Report EM-RP--WRPS-TANKFARM-2012-0014, "Potential Exists for a Large Spontaneous Gas Release Event in Deep Settled Waste Sludge"). The purpose of this technical report is to (1) present and discuss current understandings of gas retention and release mechanisms for deep sludge in U.S. Department of Energy (DOE) complex waste storage tanks; and (2) to identify viable methods/criteria for demonstrating safety relative to deep sludge gas release events (DSGRE) in the near term to support the Hanford C-Farm retrieval mission. A secondary purpose is to identify viable methods/criteria for demonstrating safety relative to DSGREs in the longer term to support the mission to retrieve waste from the Hanford Tank Farms and deliver it to the Waste Treatment and Immobilization Plant (WTP). The potential DSGRE issue resulted in the declaration of a positive Unreviewed Safety Question (USQ). C-Farm retrievals are currently proceeding under a Justification for Continued Operation (JCO) that only allows tanks 241-AN-101 and 241-AN-106 sludge levels of 192 inches and 195 inches, respectively. C-Farm retrievals need deeper sludge levels (approximately 310 inches in 241-AN-101 and approximately 250 inches in 241-AN-106). This effort is to provide analytical data and justification to continue retrievals in a safe and efficient manner.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

Functionalized magnetic nanoparticle analyte sensor

A method and system for simply and efficiently determining quantities of a preselected material in a particular solution by the placement of at least one superparamagnetic nanoparticle having a specified functionalized organic material connected thereto into a particular sample solution, wherein preselected analytes attach to the functionalized organic groups, these superparamagnetic nanoparticles are then collected at a collection site and analyzed for the presence of a particular analyte.

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

An integrated security framework for GOSS power grid analytics platform

In power grid operations, security is an essential component for any middleware platform. Security protects data against unwanted access as well as cyber attacks. GridOpticsTM Software System (GOSS) is an open source power grid analytics platform that facilitates ease of access between applications and data sources and promotes development of advanced analytical applications. GOSS contains an API that abstracts many of the difficulties in connecting to various heterogeneous data sources. A number of applications and data sources have already been implemented to demonstrate functionality and ease of use. A security framework has been implemented which leverages widely accepted, robust JavaTM security tools in a way such that they can be interchanged as needed. This framework supports the complex fine-grained, access control rules identified for the diverse data sources already in GOSS. Performance and reliability are also important considerations in any power grid architecture. An evaluation is done to determine the overhead cost caused by security within GOSS and ensure minimal impact to performance.

Gibson, Tara D.↗

DOE OSTI2014

Using analytic continuation for the hadronic vacuum polarization computation

We present two examples of applications of the analytic continuation method for computing the hadronic vacuum polarization function in space- and time-like momentum regions. These examples are the Adler function and the leading order hadronic contribution to the muon anomalous magnetic moment. We comment on the feasibility of the analytic continuation method and provide an outlook for possible further applications.

Feng, Xu↗

DOE OSTI2014

Improved Wind Turbine Drivetrain Reliability using a Combined Experimental, Computational, and Analytical Approach (Presentation)

Nontorque loads induced by the wind turbine rotor overhang weight and aerodynamic forces can greatly affect drivetrain loads and responses. If not addressed properly, these loads can result in a decrease in gearbox component life. This work uses analytical modeling, computational modeling, and experimental data to evaluate a unique drivetrain design that minimize the effects of nontorque loads on gearbox reliability: the Pure Torque drivetrain developed by Alstom. The drivetrain has a hub-support configuration that transmits nontorque loads directly into the tower rather than through the gearbox as in other design approaches. An analytical model of Alstom's Pure Torque drivetrain provides insight into the relationships among turbine component weights, aerodynamic forces, and the resulting drivetrain loads. Main shaft bending loads are orders of magnitude lower than the rated torque and are hardly affected by wind speed and turbine operations.

17 WIND ENERGY↗

DOE OSTI2015

Ultrasonic analyte concentration and application in flow cytometry

The present invention includes an apparatus and corresponding method for concentrating analytes within a fluid flowing through a tube using acoustic radiation pressure. The apparatus includes a function generator that outputs a radio frequency electrical signal to a transducer that transforms the radio frequency electric signal to an acoustic signal and couples the acoustic signal to the tube. The acoustic signal is converted within the tube to acoustic pressure that concentrates the analytes within the fluid.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

ANALYTICAL MODELING OF ELECTRON BACK-BOMBARDMENT INDUCED CURRENT INCREASE IN UN-GATED THERMIONIC CATHODE RF GUNS

In this paper we derive analytical expressions for the output current of an un-gated thermionic cathode RF gun in the presence of back-bombardment heating. We provide a brief overview of back-bombardment theory and discuss comparisons between the analytical back-bombardment predictions and simulation models. We then derive an expression for the output current as a function of the RF repetition rate and discuss relationships between back-bombardment, fieldenhancement, and output current. We discuss in detail the relevant approximations and then provide predictions about how the output current should vary as a function of repetition rate for some given system configurations.

Edelen, J. P.↗

DOE OSTI2017

Can We Practically Bring Physics-based Modeling Into Operational Analytics Tools?

We present that analytics software is increasingly used to improve and maintain operational efficiency in commercial buildings. Energy managers, owners, and operators are using a diversity of commercial offerings often referred to as Energy Information Systems, Fault Detection and Diagnostic (FDD) systems, or more broadly Energy Management and Information Systems, to cost-effectively enable savings on the order of ten to twenty percent. Most of these systems use data from meters and sensors, with rule-based and/or data-driven models to characterize system and building behavior. In contrast, physics-based modeling uses first-principles and engineering models (e.g., efficiency curves) to characterize system and building behavior. Historically, these physics-based approaches have been used in the design phase of the building life cycle or in retrofit analyses. Researchers have begun exploring the benefits of integrating physics-based models with operational data analytics tools, bridging the gap between design and operations. In this paper, we detail the development and operator use of a software tool that uses hybrid data-driven and physics-based approaches to cooling plant FDD and optimization. Specifically, we describe the system architecture, models, and FDD and optimization algorithms; advantages and disadvantages with respect to purely data-driven approaches; and practical implications for scaling and replicating these techniques. Finally, we conclude with an evaluation of the future potential for such tools and future research opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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.

Nimbalkar, Sachin U.↗

DOE OSTI2018

Techniques for controlling distance between a sample and sample probe while such probe liberates analyte from a sample region for analysis with a mass spectrometer

A system includes a mass spectrometer and associated sample interfacing equipment. The sample interfacing equipment includes a platform structured to support a sample thereon, a fluid source, a high voltage source, a dispensing probe electrically coupled to the high voltage source and defining a fluid dispensing passage therethrough, a collection probe defining a collection passage therethrough, a sensing arrangement coupled to the dispensing probe, and control logic responsive to the sensing arrangement to control distance between the dispensing probe and the sample. The dispensing probe facilitates formation of one or more ionized sample analytes when dispensing the fluid through the dispensing passage proximate to the sample on the platform. The collecting probe receives at least some of the one or more ionized sample analytes to pass through the collection passage into the mass spectrometer for analysis.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Analytical Laboratory Counting and Radiochemistry Group Equipment and Capabilities

The Analytical Laboratory at the Materials and Fuels Complex provides quality analytical results through a variety of instrumental methods. The work of the Counting and Radiochemistry Group focuses on several instrumental techniques: Gamma Spectrometry, Liquid Scintillation Counting, Gas Flow Proportional Counting, and Alpha Spectrometry. This talk will focus on an overview of the Counting and Radiochemistry's capabilities, and will briefly discuss some of the sample preparation methods currently in use by the group.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Ultrasonic analyte concentration and application in flow cytometry

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Principles of Corrosion in Nuclear Systems: Theory and Analytical Methods

This article is meant to provide the reader with the fundamental electrochemistry necessary to critically evaluate the data and discussions in the articles on corrosion that follow. As such it has two main sections, theory and analytical methods. In the section on theory, a review of half cell reactions, cell potentials and the Nernst equation, and reference electrodes in nuclear systems are discussed. In addition, a review of the thermodynamics from room temperature to the PWR and kinetics of dissolution and passive film formation is also presented. In the section on analytical methods, we review the principles of potentiodynamic polarization, electrochemical impedance spectroscopy, and we introduce a more seldom used technique, Mott-Schottky analysis.

Lillard, R Scott↗

DOE OSTI2020

On the Feasibility of Using Reduced-Precision Tensor Core Operations for Graph Analytics

Today’s data-driven analytics and machine learning workload have been largely driven by the General-PurposeGraphics Processing Units (GPGPUs). To accelerate dense matrix multiplications on the GPUs, Tensor Core Units (TCUs) have been introduced in recent years. In this paper, we study linear-algebra-based and vertex-centric algorithms for various graph kernels on the GPUs with an objective of applying this new hardware feature to graph applications. We identify the potential stages in these graph kernels that can be executed on the Tensor Core Units. In particular, we leverage the reformulation of the reduction and scan operations in terms of matrix multiplication [1]on the TCUs. We demonstrate that executing these operations on the TCUs, available inside different graph kernels, can assist in establishing an end-to-end pipeline on the GPGPUs without depending on hand-tuned external libraries and still can deliver comparable performance for various graph analytics.

Graph algorithms, GPU computing↗

DOE OSTI2020

Towards Trust-Augmented Visual Analytics for Data-Driven Energy Modeling

The promise of data-driven predictive modeling is being increasingly realized in various science and engineering disciplines, where experts are used to the more conventional, simulation-driven modeling practices. However, trust remains a bottleneck for greater adoption of machine learning-based models for domain experts, who might not be necessarily trained in data science. In this paper, we focus on the building energy domain, where physics-based simulations are being complemented or replaced by machine learning-based methods for forecasting energy supply and demand at various spatio-temporal scales. We study the trust problem in close collaboration with energy scientists and engineers and describe how visual analytics can be leveraged for alleviating this trust bottleneck for stakeholders with varying degrees of expertise and analytics goals in this domain.

Kandakatla, Akshith R.↗