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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An adaptive masking method for beam halo measurement by a digital micro mirror device

We report that in high intensity particle beams, irregularities in cathode emission, scattering effects, dark current and space charge forces can lead to a common phenomenon termed beam halo with associated emittance growth, beam loss and overall beam quality degradation. It is of fundamental interest and practical importance to precisely monitor such beam halo, which could offer valuable insights into the experimental strategy for the suppression of this undesired feature. A Digital Micro mirror Device (DMD) is a computer-controlled micro-electrical-mechanical system that contains a compact array of physically independent reflective mirrors. Using a standard DMD, we come up with an adaptive masking method for halo measurement, which demonstrates superior robustness and efficiency comparing to the conventional approaches as confirmed by simulation and experimental results. Our development includes an integrated package of hardware, software and a graphic user interface (GUI) that is robust and portable and can be applied as a beam halo diagnostic for electron guns or radiating charged particle beams in general.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Robust Adaptive Decentralized Dynamic State Estimation with Unknown Control Inputs using Field PMU Measurements

This paper proposes a robust adaptive decentralized dynamic state estimation method for power system with unknown inputs of the highly detailed synchronous machine model. The temporal and spatial correlations among the unknown inputs are used to derive a vector auto-regressive model. The latter is further integrated together with state transition and measurement models for joint state and unknown inputs estimation. Thanks to the consideration of implicit cross-correlations between the states and the unknown inputs, only generator terminal voltage and current phasors are needed. Test results on the US WECC system using the field PMU measurements show that the proposed method is able to track both the system dynamic states and unknown controller inputs. These information could significantly benefit the validation and calibration of generator controller parameters.

Zhao, Junbo↗
DOE OSTI2023

Measurement-based quantum simulation of Abelian lattice gauge theories

Numerical simulation of lattice gauge theories is an indispensable tool in high energy physics, and their quantum simulation is expected to become a major application of quantum computers in the future. In this work, for an Abelian lattice gauge theory in d d spacetime dimensions, we define an entangled resource state (generalized cluster state) that reflects the spacetime structure of the gauge theory. We show that sequential single-qubit measurements with the bases adapted according to the former measurement outcomes induce a deterministic Hamiltonian quantum simulation of the gauge theory on the boundary. Our construction includes the (2+1) ( 2 + 1 ) -dimensional Abelian lattice gauge theory simulated on three-dimensional cluster state as an example, and generalizes to the simulation of Wegner’s lattice models M_{(d,n)} M ( d , n ) that involve higher-form Abelian gauge fields. We demonstrate that the generalized cluster state has a symmetry-protected topological order with respect to generalized global symmetries that are related to the symmetries of the simulated gauge theories on the boundary.Our procedure can be generalized to the simulation of Kitaev’s Majorana chain on a fermionic resource state. We also study the imaginary-time quantum simulation with two-qubit measurements and post-selections, and a classical-quantum correspondence, where the statistical partition function of the model M_{(d,n)} M ( d , n ) is written as the overlap between the product of two-qubit measurement bases and the wave function of the generalized cluster state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Reducing measurement costs by recycling the Hessian in adaptive variational quantum algorithms

Abstract Adaptive protocols enable the construction of more efficient state preparation circuits in variational quantum algorithms (VQAs) by utilizing data obtained from the quantum processor during the execution of the algorithm. This idea originated with Adaptive Derivative-Assembled Problem-Tailored variational quantum eigensolver (ADAPT-VQE), an algorithm that iteratively grows the state preparation circuit operator by operator, with each new operator accompanied by a new variational parameter, and where all parameters acquired thus far are optimized in each iteration. In ADAPT-VQE and other adaptive VQAs that followed it, it has been shown that initializing parameters to their optimal values from the previous iteration speeds up convergence and avoids shallow local traps in the parameter landscape. However, no other data from the optimization performed at one iteration is carried over to the next. In this work, we propose an improved quasi-Newton optimization protocol specifically tailored to adaptive VQAs. The distinctive feature in our proposal is that approximate second derivatives of the cost function are recycled across iterations in addition to optimal parameter values. We implement a quasi-Newton optimizer where an approximation to the inverse Hessian matrix is continuously built and grown across the iterations of an adaptive VQA. The resulting algorithm has the flavor of a continuous optimization where the dimension of the search space is augmented when the gradient norm falls below a given threshold. We show that this inter-optimization exchange of second-order information leads the approximate Hessian in the state of the optimizer to be consistently closer to the exact Hessian. As a result, our method achieves a superlinear convergence rate even in situations where the typical implementation of a quasi-Newton optimizer converges only linearly. Our protocol decreases the measurement costs in implementing adaptive VQAs on quantum hardware as well as the runtime of their classical simulation.

Ramôa, Mafalda (ORCID:0000000302187801)↗
DOE OSTI2020

Real Time Applications Using Linear State Estimation Technology (RTA/LSE)

Electric Power Group, LLC (EPG) was awarded DOE OE0000849 to design, develop, and demonstrate three real-time applications for monitoring power system stability. The applications use phasor measurements and processing by a linear state estimator (LSE) to improve system visibility and accuracy. These applications leverage the large and expanding phasor measurement systems being deployed by utilities throughout the world, and specifically in the United States. Phasor measurements provide a much more detailed view of the power systems than traditional SCADA systems, so can provide better visibility of events and an early warning of developing problems. These three applications are real-time contingency analysis (RTCA), area angle monitoring (AAM), and a voltage stability index (VSI). The project was fully completed as proposed. All three applications were successfully implemented and demonstrated. There were challenges the caused project delays, however. While the RTCA is based on well-known concepts and readily available tools, its deployment using phasor measurements meant it needed to be adapted to sometimes sparse measurements and limited coverage areas. EPG met these challenges with extensive modeling and testing. The AAM is based on unproven research, so EPG had to deal with a lot of unknowns and develop additional methods for practical implementation. These activities took more time than anticipated, so required extra time for development. In addition, there was difficulty getting adequate measurement locations for successful deployment and utility installation delays. Consequently, the project required a time extension to complete. These three real-time applications, RTCA, AAM, and VSI, use only phasor measurement input. Since they do not require the EMS or other measurement systems, they can serve as a backup and security check for the EMS. Phasor measurements are validated and extended by an LSE. The LSE will always produce an output even when some inputs are impaired, so the RT applications will operate even when the EMS state estimator does not converge and the applications it supports cannot function. Consequently, these RT applications can provide valuable additional reliability for control center operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Adaptive estimation of quantum observables

The accurate estimation of quantum observables is a critical task in science. With progress on the hardware, measuring a quantum system will become increasingly demanding, particularly for variational protocols that require extensive sampling. Here, we introduce a measurement scheme that adaptively modifies the estimator based on previously obtained data. Our algorithm, which we call AEQuO, continuously monitors both the estimated average and the associated error of the considered observable, and determines the next measurement step based on this information. We allow both for overlap and non-bitwise commutation relations in the subsets of Pauli operators that are simultaneously probed, thereby maximizing the amount of gathered information. AEQuO comes in two variants: a greedy bucket-filling algorithm with good performance for small problem instances, and a machine learning-based algorithm with more favorable scaling for larger instances. The measurement configuration determined by these subroutines is further post-processed in order to lower the error on the estimator. We test our protocol on chemistry Hamiltonians, for which AEQuO provides error estimates that improve on all state-of-the-art methods based on various grouping techniques or randomized measurements, thus greatly lowering the toll of measurements in current and future quantum applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

High-yield magnetic recoil neutron spectrometer on the National Ignition Facility for operation up to 60 MJ

We report that recent progress at the National Ignition Facility (NIF), with neutron yields of order 1 x 10 17 , places new constraints on diagnostics used to characterize implosion performance. The Magnetic Recoil neutron Spectrometer (MRS), which is routinely used to measure yield, ion temperature (T ion ), and down-scatter ratio (dsr), has been adapted to allow measurements of dsr up to 5 x 10 17 , and yield and T ion up to 2 x 10 18 in the near term with new data processing techniques and conversion foil solutions. This paper presents a solution for extending MRS operation up to a yield of 2 x 10 19 (60 MJ) by moving the spectrometer outside of the NIF shield wall. This will not only enhance the upper yield limit by 10x but also improve signal-to-background by 5x.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Melting temperature measurement of refractory oxide ceramics as a function of oxygen fugacity using containerless methods

An aerodynamic conical nozzle levitator (CNL) has been used to measure the melting temperatures of refractory ceramics. The well-established method of cooling traces has been adapted to allow measurements for air-sensitive samples using a controlled atmosphere, where the oxygen partial pressure can be adjusted and monitored in real time. In this study, we explain the details of a system that we developed for use at the Spallation Neutron Source (Oak Ridge National Laboratory). Measurements of the melting behavior of (Fe,Cr,Al) 3 O 4 spinels were made between log (PO 2 (atm)) of -0.7 and -5. The melting temperature of hercynite is found to be oxygen potential dependent, ranging between 1692 and 1767°C at log (PO 2 ) values from -4.42 to -0.70.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Leaf gas exchange, leaf water potential and spectral reflectance, BIONTE, Brazil, 2023

Leaf traits measured at the top of the canopy on 30 tree species in the BIONTE experimental forest, near Manaus, Brazil, at three time points during August to November, 2023. The aim of this study was to test the relationship between leaf water use efficiency and wood density. Leaf gas exchange was measured on top-of-canopy leaves accessed by an articulated boom lift. Response curves (A-Ci and A-Q), and dark adapted respiration were measured on cut branches. Survey gas exchange measurements were performed on attached leaves at various times during the day. Following gas exchange, leaves were harvested, and measured for leaf water potential and spectral reflectance. Data in this data package is presented in csv files, with metadata in csv and descriptive experimental protocols as pdf. Gas exchange data and metadata meets the requirements of the ESS-DIVE reporting format for leaf-level gas exchange data and metadata.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Commitment to Hypertension Control During the COVID-19 Pandemic: Million Hearts Initiative Exemplars

Hypertension is a major risk factor for cardiovascular diseases, but 3 of 4 US adults do not have their blood pressure adequately controlled. Million Hearts (US Department of Health and Human Services) is a national initiative that promotes a set of priorities and interventions to optimize delivery of evidence-based strategies to manage cardiovascular disease, including hypertension. The COVID-19 pandemic, however, has disrupted routine care and preventive service delivery. We identified examples of clinical and health organizations that adapted services and care processes to continue a focus on monitoring and controlling hypertension during the pandemic. Eight Hypertension Control Exemplars were identified and interviewed. They reported various adapted care strategies including telemedicine, engaging patients in self-measured blood pressure monitoring, adapting or implementing medication management services, activating partnerships to respond to patient needs or expand services, and implementing unique patient outreach approaches. Documenting these hypertension control strategies can help increase adoption of adaptive approaches during public health emergencies and routine care.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Transfer learning for analysis of collective and non-collective Thomson scattering spectra

Thomson scattering (TS) diagnostics provide reliable, minimally perturbative measurements of fundamental plasma parameters, such as electron density (⁠n e ) and electron temperature (⁠T e ⁠). Deep neural networks can provide accurate estimates of ⁠n e and T e when conventional fitting algorithms may fail, such as when TS spectra are dominated by noise, or when fast analysis is required for real-time operation. Although deep neural networks typically require large training sets, transfer learning can improve model performance on a target task with limited data by leveraging pre-trained models from related source tasks, where select hidden layers are further trained using target data. We present five architecturally diverse deep neural networks, pre-trained on synthetic TS data and adapted for experimentally measured TS data, to evaluate the efficacy of transfer learning in estimating n e and T e in both the collective and non-collective scattering regimes. We evaluate errors in n e and T e estimates as a function of training set size for models trained with and without transfer learning, and we observe decreases in model error from transfer learning when the training set contains ≲ 200 experimentally measured spectra.

Artificial neural networks↗
DOE OSTI2020

Implementation of Talbot–Lau x-ray deflectometry in the pulsed power environment using a copper X-pinch backlighter

A Talbot–Lau x-ray deflectometer can map electron density gradients in high energy density plasmas, as well as provide information about plasma elemental composition through single-image x-ray refraction and attenuation measurements. A new adaptation to a pulsed power environment used backlighting from copper X-pinches, allowing for electron density mapping of a low-Z object. Even though the X-pinch backlighter is not properly optimized for emitting x-rays in terms of source size and photon fluence, Moire fringe patterns with contrast up to 14% and fringe shift due to refraction on a beryllium object are obtained. Due to the proximity of the deflectometer with the X-pinch (~6 cm), it is shown that a protective filter is required to avoid damage in the closest (i.e., source) grating due to both plasma debris and mechanical shock. Regarding grating survival, these did not show any damage due to the intense magnetic field or heating induced by plasma radiation. Electron density on beryllium was measured with a difference lower than 16%. The areal electron density mapping of the sample was limited by source size characteristics, in similarity to transmission radiography. These results show the potential of plasma electron density as well as material mapping through Talbot–Lau x-ray deflectometry in a pulsed power environment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Extended real-time voltage instability identification method based on synchronized phasor measurements

This paper presents an extended adaptive approach designed to accurately estimate the Thévenin equivalent parameters using phasor measurements at a given bus for measurements lying in any of four quadrants of the PQ-plane. The improvement is achieved by using a new condition to properly update the estimated parameters after an initial guess. Based on an adaptive philosophy, the proposed approach can correctly account for the intrinsic nonlinearities of a power system, can provide a real-time estimation of Thévenin parameters, and does not require network topology knowledge. The method is validated using the Kundur 2-area system, showing estimation improvements compared to the current adaptive approach and the classical recursive least-squares method. The proposed approach is able to estimate both sides of the system with respect to the measurement bus. In addition, a data-driven voltage stability index is developed. To illustrate the performance of the proposed approach in a larger power system, a voltage stability assessment is carried out on the IEEE 39-bus system, considering the action of overexcitation limiters of generators and nonlinear loads. The proposed approach is suitable for applications that require an accurate Thévenin equivalent estimation in real-time, such as for voltage stability assessment. The new approach provides a reliable tool for the system operators to make proper and timely decisions.

42 ENGINEERING↗
DOE OSTI2020

Hydrostatic and Uniaxial Pressure Tuning of Iron-Based Superconductors: Insights into Superconductivity, Magnetism, Nematicity, and Collapsed Tetragonal Transitions

Iron-based superconductors are well-known for their intriguing phase diagrams, which manifest a complex interplay of electronic, magnetic and structural degrees of freedom. Among the phase transitions observed are superconducting, magnetic, and several types of structural transitions, including a tetragonal-to-orthorhombic and a collapsed-tetragonal transition. In particular, the widely-observed tetragonal-to-orthorhombic transition is believed to be a result of an electronic order that is coupled to the crystalline lattice and is, thus, referred to asnematic transition. Nematicity is therefore a prominent feature of these materials, which signals the importance of the coupling of electronic and lattice properties. Correspondingly, these systems are particularly susceptible to tuning via pressure (hydrostatic, uniaxial, or some combination). We review efforts to probe the phase diagrams of pressure-tuned iron-based superconductors, with a strong focus on our own recent insights into the phase diagrams of several members of this mate-rial class under hydrostatic pressure. These studies on FeSe, Ba(Fe 1-x Co x ) 2 As 2 , Ca(Fe 1-x Co x ) 2 As 2 and CaK(Fe 1-x Ni x ) 4 As 4 were, to a significant extent, made possible by advances of what measurements can be adapted to the use under differing pressure environments. We point out the potential impact of these tools for the study of the wider class of strongly correlated electron systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Household energy resilience in extreme weather events: An investigation of energy service importance, HVAC usage behaviors, and willingness to pay

Household energy resilience, particularly maintaining essential energy services within an acceptable and affordable level, is critical during extreme weather events (e.g., winter storms, heat waves) with power shortages or outages. However, the research on the importance and acceptable compromise levels of energy services, HVAC usage behavior changes, and willingness to pay (WTP) for energy services during disasters is limited. Therefore, this study investigates the importance and compromise of household energy services, HVAC usage behaviors, and WTP, as three key dimensions of household energy resilience, in both normal days and disaster scenarios through surveys (n=485). First, 12 common residential end-uses are grouped into high, mid, and low-priority services using hierarchical clustering, in which high-priority services (perceived as important and un-compromisable) include food cooking and storage (refrigerator and freezer) and thermal comfort (space heating and cooling), mid-priority services involve water heating and lighting, while low-priority services are mostly related to entertainment and housework (e.g., TV, laundry). Also, HVAC use patterns demonstrate that occupants become more energy conservative during disasters, e.g., reducing durations of running HVAC and adjusting temperature setpoints to save energy. In terms of energy cost, approximately 60% of respondents are willing to pay more to maintain energy services during disasters, although only 13% are prepared to pay over double the normal energy prices. The regression models further reveal that household energy resilience varies across different sociodemographic groups (e.g., age, income, family size) and is impacted by disaster experience and beliefs in clean energy and climate. In conclusion, these research findings provide important perspectives to understand household energy resilience and inform measures for disaster adaptation of households in extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Enabling Microscale Processing: Combined Raman and Absorbance Spectroscopy for Microfluidic On-Line Monitoring

Microfluidics have many potential applications including characterization of chemical processes on a reduced scale, spanning the study of reaction kinetics using on-chip liquid–liquid extractions, sample pretreatment to simplify off-chip analysis, and for portable spectroscopic analyses. The use of in situ characterization of process streams from laboratory-scale and microscale experiments on the same chemical system can provide comprehensive understanding and in-depth analysis of any similarities or differences between process conditions at different scales. A well-characterized extraction of Nd(NO 3 ) 3 from an aqueous phase of varying NO 3– (aq) concentration with tributyl phosphate (TBP) in dodecane was the focus of this microscale study and was compared to an earlier laboratory-scale study utilizing counter current extraction equipment. Here, we verify that this same extraction process can be followed on the microscale using spectroscopic methods adapted for microfluidic measurement. Concentration of Nd (based on UV–vis) and nitrate (based on Raman) was chemometrically measured during the flow experiment, and resulting data were used to determine the distribution ratio for Nd. Extraction distributions measured on the microscale were compared favorably with those determined on the laboratory scale in the earlier study. Both micro-Raman and micro-UV–vis spectroscopy can be used to determine fundamental parameters with significantly reduced sample size as compared to traditional laboratory-scale approaches. This leads naturally to time, cost, and waste reductions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗