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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 361 records · Page 20

Measurement of Neutron Multiplicity in Charged Current Neutrino Interactions on Oxygen

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a 26-ton gadolinium-doped water Cherenkov detector located 100~meters downstream in the Booster Neutrino Beam (BNB) at the Fermi National Accelerator Laboratory (Fermilab). Its primary goals are to (1) measure the neutron yield from $\nu_\mu$ interactions as a function of momentum transfer $Q^2$ so that neutrino-nucleus interaction models can be better constrained, and (2) demonstrate the power of novel, fast-timing detectors with the first deployment of Large Area Picosecond PhotoDetectors (LAPPDs). Current knowledge of neutrino-nucleus interactions fall short in modeling the topologies of such interactions, leading to inaccurate reconstruction of event kinematics such as particle energy, direction, and vertex. As a consequence, the accuracy of cross section measurements is impacted, which is necessary for precise physics measurements. Neutrons are an indication of inelasticity and affect the determination of the energy of the parent neutrino. Quantifying the neutron yield is a step towards reducing the associated uncertainties, and thus improving our understanding of these complex interactions and benefiting the next generation of long-baseline neutrino experiments. ANNIE will make use of LAPPDs to measure neutron multiplicity of CC-0$\pi$ $\nu_\mu$ interactions on oxygen, making it the first experiment to deploy an array of these photodetectors. Because the LAPPD is a novel photodetection technology, much customization is required to integrate it into existing electronics. The first half of this thesis covers the significant progress made towards the first deployment of the LAPPD system. From its test stand at Fermilab, the LAPPD system was systematically tested and put together until deployment readiness was achieved. I present my contributions to the design, fabrication, and testing of the waterproof housing and cables, and the commissioning of the LVHV board that powers the LAPPD and its readout electronics. These efforts brought the LAPPD system significantly closer to deployment, and eventually first data. The second half of this thesis presents the vertex and energy reconstruction algorithms developed to analysis the beam data with PMT-only information. While much progress has been made towards the deployment of LAPPDs, with several in the detector tank, efforts to integrate the LAPPD datastream are in progress. Thus, I developed a ring edge detection technique using PMT data to fit the muon vertex and determine its energy. The analysis in this thesis finds average neutron yields of $\Bar{n}_{data} = 0.452 \pm 0.039 (\text{stat}) \pm 0.27 (\text{sys})$ for a selection of muon neutrino candidates in the fiducial volume of ANNIE and corrected with an averaged neutron detection efficiency. An equivalent analysis for simulated beam data results in an average neutron yield of $\Bar{n}_{MC} = 0.582 \pm 0.018 (\text{stat}) \pm 0.25 (\text{sys})$. Future work includes application of efficiency corrections at a positional level, quantification of all systematic uncertainties, and neutron multiplicity measurements with other event topologies.

43 PARTICLE ACCELERATORS↗

System for multiple burns from a rocket motor

A system for multiple burns from a solid fuel rocket motor may extinguish rocket fuel after the rocket has been ignited. The motor may be extinguished via rapid decompression of the combustion chamber. The fuel may then be reignited by a suitable igniter, and the process of extinguishing and reigniting may be repeated, enabling multi-burn maneuvers. A decompressive extinguishing plug nozzle may extinguish solid rocket fuel after the rocket has been ignited and/or keep a rocket in a disarmed (zero thrust) state until the rocket is to be armed. The nozzle may include a plug that mostly impedes the opening of the nozzle and an outer cowl that is movable to rapidly decompress the combustion chamber. This rapid decompression extinguishes the solid rocket fuel. In some aspects, the fuel can be reignited and extinguished multiple times.

Dallmann, Nicholas↗

Two-Tower Quantum Matrix Chain Multiplication: Trading Qubits for Depth

Matrix chain multiplication -- computing $\mathcal{W} = M^{(0)}\cdots M^{(K-1)}$ where $M^{(k)} \in \mathbb{R}^{P_k \times P_{k+1}}$-- arises in scientific computing, machine learning, and graph analysis. Despite the importance of this problem, for chains of distinct matrices, the classical number of operations grows linearly with the chain length $K$ and polynomially in the matrix dimensions. We present \emph{Two-Tower Matrix Multiplication}, a quantum subroutine that encodes the product $\mathcal{W}$ of the $K$ matrices into a quantum state in circuit depth $\mathcal{O}(\max_{k} \mathrm{polylog} (P_k P_{k+1}))$, which is independent of~$K$ within the QRAM-based state-preparation model, whereas the qubit count is $\mathcal{O}\bigl(\sum_{k} \log P_k \bigr)$; the total gate count remains linear in $K$, so the gain is in the circuit depth. The construction interleaves state-preparation operators across two layers; within each layer, all operators act on disjoint registers and execute in parallel. This subroutine can be specialized for the chain-vector case, which computes the product of $K-1$ matrices applied to a vector. We prove the correctness of the subroutine for all $K$ and provide two implementations using the Qiskit and QCLAB frameworks. The subroutine is applicable to any downstream quantum algorithm that operates on a matrix encoded in the statevector, including norm estimation, graph-matrix powers, linear system solving, and quantum machine learning kernels.

Antonioli, Giacomo [Pisa U.] (ORCID:00090000668703↗

Bemnifosbuvir: An HCV NS5B Inhibitor With Multiple Modes of Action

Bemnifosbuvir (BEM) is a potent, pan-genotypic inhibitor targeting the hepatitis C virus (HCV) NS5B polymerase. Its antiviral activity was evaluated in an ascending dose phase I clinical trial involving 30 patients treated once a day for 7 days. After treatment initiation, plasma HCV RNA declined in a biphasic manner with a mean reduction of 2.3 log 10 IU/mL after 24 hours and 4.4 log10 IU/mL by day 7 for the highest dose. Alanine aminotransferase (ALT) also normalized in most patients. We employed a multiscale mathematical model fitted to the HCV RNA and ALT dynamics to quantify the antiviral activity and evaluate the modes of action of BEM. We found that models in which BEM only acted as a typical HCV RNA polymerase inhibitor and reduced the intracellular production of HCV RNA did not fit the data as well as models in which BEM had multiple modes of action, including suppressing viral assembly and secretion and enhancing intracellular HCV RNA degradation. BEM's effectiveness in inhibiting intracellular HCV RNA production increased with dose (150 mg/day: 88.2%, 300 mg/day: 98.8%, 600 mg/day: 99.5%), while inhibition of viral assembly and release was ~95% effective regardless of dose. We observed a dose-dependent enhancement in the degradation of intracellular HCV RNA, with degradation rates 1.5-fold higher in patients receiving 300 mg/day and 2.7-fold higher in those receiving 600 mg/day than in patients receiving 150 mg/day. No significant differences in antiviral activity were detected between HCV genotypes 1b and 3 or between patients with and without compensated cirrhosis.

59 BASIC BIOLOGICAL SCIENCES↗

Enhanced mobility of dislocation network nodes and its effect on dislocation multiplication and strain hardening

Understanding plastic deformation of crystals in terms of the fundamental physics of dislocations has remained a grand challenge in materials science for decades. To overcome this, the Discrete Dislocation Dynamics (DDD) method has been developed, but its lack of atomistic resolution leaves open the possibility that certain key mechanisms may be overlooked. Here, by comparing large-scale Molecular Dynamics (MD) with DDD simulations performed under identical conditions we uncover significant discrepancies in the predicted strength and microstructure evolution in BCC crystals under high-strain rate conditions. These are traced to unexpected behaviors of dislocation network nodes forming at dislocation intersections, that can move in ways not previously anticipated as revealed by MD. Once these newfound freedoms of nodal motion are incorporated, DDD simulations begin to closely match plastic evolution observed in MD. This additional mechanism of motion whereby non-screw dislocations can change their glide plane profoundly affects fundamental processes of dislocation multiplication, recovery and storage that define strength of metals.

36 MATERIALS SCIENCE↗

Boron coated straw-based neutron multiplicity counter for neutron interrogation of TRISO fueled pebbles

Pebble bed reactors (PBRs) can improve the safety and economics of the nuclear energy production. PBRs rely on TRIstructural-ISOtropic (TRISO) fuel pebbles for enhanced fission product retention. Accurate characterization of individual fuel pebbles would enable the validation of computational models, efficient use of TRISO fuel, and improve fuel accountability. Here, we have developed and tested a new neutron multiplicity counter (NMC) based on 192 boron coated straw (BCS) detectors optimized for 235 U assay in TRISO fuel. The new design yielded a singles and doubles neutron detection efficiency of 4.71% and 0.174%, respectively, and a die-away time of 16.7 μs. The NMC has a low intrinsic gamma-ray detection efficiency of 8.71 x 10 –8 at an exposure rate of 80.3 mR/h. In simulation, a high-efficiency version of the NMC encompassing 396 straws was able to estimate the 235 U in a pebble with a relative uncertainty and error both below 2% in 100 s.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Coherent multiple scattering of out-of-equilibrium interacting Bose gases

We review recent theoretical and experimental progresses in the coherent multiple scattering of weakly interacting disordered Bose gases. These systems have allowed, in the recent years, a characterization of weak and strong localization phenomena in disorder at an unprecedented level of control. In this paper, we first discuss the main physical concepts and recent experimental achievements associated with a few emblematic “mesoscopic” effects in disorder like coherent backscattering, coherent forward scattering or mesoscopic echos, focusing on the context of out-of-equilibrium cold-atom setups. We then address the role of weak particle interactions and explain how, depending on their relative strength with respect to the disorder and on the time scales probed, they can give rise to a dephasing mechanism for weak localization, thermalize a non-equilibrium Bose gas or make it become a superfluid.

74 ATOMIC AND MOLECULAR PHYSICS↗

HomPINNs: Homotopy physics-informed neural networks for learning multiple solutions of nonlinear elliptic differential equations

Physics-informed neural networks (PINNs) based machine learning is an emerging framework for solving nonlinear differential equations. However, due to the implicit regularity of neural network structure, PINNs can only find the flattest solution in most cases by minimizing the loss functions. In this paper, we combine PINNs with the homotopy continuation method, a classical numerical method to compute isolated roots of polynomial systems, and propose a new deep learning framework, named homotopy physics-informed neural networks (HomPINNs), for solving multiple solutions of nonlinear elliptic differential equations. The implementation of an HomPINN is a homotopy process that is composed of the training of a fully connected neural network, named the starting neural network, and training processes of several PINNs with different tracking parameters. The starting neural network is to approximate a starting function constructed by the trivial solutions, while other PINNs are to minimize the loss functions defined by boundary condition and homotopy functions, varying with different tracking parameters. These training processes are regraded as different steps of a homotopy process, and a PINN is initialized by the well-trained neural network of the previous step, while the first starting neural network is initialized using the default initialization method. Finally, several numerical examples are presented to show the efficiency of our proposed HomPINNs, including reaction-diffusion equations with a heart-shaped domain.

97 MATHEMATICS AND COMPUTING↗

Additive manufacturing of continuous carbon fiber-reinforced SiC ceramic composite with multiple fiber bundles by an extrusion-based technique

Due to the high cost, complex preparation process and difficulty in structural design, the traditional methods for carbon fiber-reinforced SiC ceramic composite preparation have great limitations. This paper presents a technique for the additive manufacturing multiple continuous carbon fiber bundle-reinforced SiC ceramic composite with core-shell structure using an extrusion-based technique. A conventional nozzle system was modified to print simultaneously a water-based SiC paste with continuous carbon fibers. Different levels of binder contents were investigated to optimize the stickiness, viscosity, thixotropy and viscoelasticity of the paste. After sintering, SiC whiskers were generated on the surface of fiber, which is conjectured to be due to the reaction between SiO and carbon fiber at high temperature. The continuous carbon fiber-reinforced SiC ceramic composite exhibited non-brittle fracture. In conclusion, the flexural strength of the additively manufactured Cf/SiC composites improved from 162 MPa with no fiber bundles to a maximum of 219 MPa with three fiber bundles.

36 MATERIALS SCIENCE↗

A direct transcription-based multiple shooting formulation for dynamic optimization

The growing need for fast and efficient solution techniques for solving dynamic optimization problems is driven by a broad spectrum of applications in scheduling and control. We suggest a novel framework for dynamic optimization that utilizes a multiple shooting “backbone” with discrete rather than continuous subproblems, thereby eliminating need for repeated time-integration. A Lagrangian relaxation (LR)-based decomposition scheme is proposed, which dualizes the state continuity requirements between subproblems and enables parallel solution of the problem. We demonstrate the applicability of our method on two case studies: the Van der Pol oscillator and a batch reactor.

42 ENGINEERING↗

MITNS: Multiple-Ion Transport Numerical Solver for magnetized plasmas

MITNS (Multiple-Ion Transport Numerical Solver) is a new numerical tool designed to perform 1D simulations of classical cross-field transport in magnetized plasmas. Furthermore, its detailed treatment of multi-species effects makes it a unique tool in the field. We describe the physical model it simulates, as well as its numerical implementation and performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

How to avoid multiple scattering in strongly scattering SANS and USANS samples

Small Angle Neutron Scattering (SANS) and Ultra Small Angle Neutron Scattering (USANS) are the only available experimental techniques to provide seamless non-destructive measurements of the geometry of the accessible and inaccessible pore structure of rocks from sub-nanopore size to the scale of macropores. They have therefore become the measurement of choice for tight reservoir rocks such as organic rich shales. A simplifying assumption in the analysis is, however, that during the path of neutrons through the sample each neutron is only scattered once. Shales are samples with a high scattering power and Multiple Scattering (MS) may occur which requires special modelling for deconvolution of the results. The approach to avoid MS is to simply reduce the sample thickness to <0.15–0.5 mm. Here, in this work, we present a systematic method on wavelength selection and preparation of samples to optimise extraction of microstructural data and minimise parasitic errors. Experimentally measured SAS transmission (TSAS) values are used as a practical criterion for estimation of the extent of MS. Generous beamtime allocations allowed robust testing revealing that sample thicknesses can be twice as thick as predicted using the standard protocol. Analysing thicker samples is particularly beneficial for statistically relevant characterisation of heterogeneous samples making the new protocol the method of choice for such samples.

(U)SANS↗

Modeling the dynamic response of rock masses with multiple compliant fluid saturated joint sets - Part II: Continuum modeling

Part I of this two-part paper describes enhancements of a mesoscale model to include: many non-persistent fluid saturated joints with finite area, normal compliance with hysteresis and the weakening effects of angular deviation in the joint sets and of fluid pressure in the joints. The objective of this Part II is to use the results of the mesoscale model as simulated data to inspire functional forms in a continuum model for rock masses with multiple compliant fluid saturated joint sets which include these enhancements. Also, an algorithm is proposed for reducing the number of joint sets being modeled. Examples are presented here which show that the continuum model can predict similar anisotropic response to that observed in mesoscale simulations. In contrast with the mesoscale model, the continuum model can be used for large scale simulations of real applications, smoothly transitioning from coupled inelastic thermomechanical response near an explosive source to orthotropic elastic response far from the source.

58 GEOSCIENCES↗

Multiple-charging effects on the CCN activity and hygroscopicity of surrogate black carbon particles

Accurate measurements of cloud condensation nuclei (CCN) activity and hygroscopicity of black carbon (BC)-containing particles are particularly important because of the positive climate forcing from these particles. Such measurements are typically conducted on particles selected by a Differential Mobility Analyzer (DMA), which in addition to singly charged particles transmits multiply charged larger particles that have the same electrical mobility. These larger particles activate at lower supersaturations than the singly charged particles, biasing measurements and resulting in overestimation of CCN activity and hygroscopicity parameter (κ). Here, we measure the CCN activity and determine κ for different BC surrogates with electrical mobility diameters from 100 to 200 nm selected 1) only by electrical mobility with a DMA, and 2) by both electrical mobility and mass using a DMA and a Centrifugal Particle Mass Analyzer (CPMA), thus allowing selection of only singly charged particles. We demonstrate the use of the DMA-CPMA system in resolving biases caused by multiply charged particles, and we show that the effect of multiple charging on the CCN activity of the BC particles is strongly influenced by morphology dispersion, i.e., the variability due to the range of morphologies of particles that have the same electrical mobility and mass. Finally, our findings show that electrical mobility-based methods alone are unlikely to lead to accurate results in measurements of CCN activation and hygroscopicity of BC particles, even for those with a more compact morphology.

54 ENVIRONMENTAL SCIENCES↗

Multiple Coulomb scattering in acrylic of a 221.3 MeV therapeutic proton beam

Measurements of multiple Coulomb scattering (MCS) distributions for 221.3 MeV therapeutic protons are presented using a novel detector system comprised of a thin scintillator, a pellicle mirror, and a digital camera. The MCS distributions were characterized for three acrylic phantoms of varying lengths and for two biological density-equivalent phantoms simulating bone and muscle. Additionally, beam profiles were measured across an energy range of 80.3–221.3 MeV in 20 MeV increments. The observed energy dependence of the photon yields is consistent with the tabulated stopping power values. Finally, the experimental results are benchmarked against Geant4 simulations, demonstrating consistent agreement and validating the capability of the detector system for radiology measurements.

Digital camera↗

Generating multiple benefits from forests by producing value-added products: Lessons from the Pacific Northwestern US

This paper asks what conditions are needed to counteract a declining forest industry. The mobilization of supply chains for new value-added forest products and services can be supported by programs designed to simultaneously achieve multiple goals related to health, climate, and rural economic development. But several challenges are identified that underscore the need to stack benefits and incentives to achieve muti-sectoral goals. Based on a case study in Washington state, we find opportunities and constraints for sourcing forest products are determined by the local and regional conditions such as availability of working forests and their residues, socioeconomic conditions, workforce availability, transportation options, and perceptions about social license of the new industry. Key recommendations are the need for (1) a consistent demand and resilient supply chain for the new product; (2) a stable, supportive policy and assessment framework; (3) timely, transparent, and trusted monitoring and reporting of benefits and costs; (4) fostering engagement and buy-in from stakeholders; (5) a context-specific evaluation of opportunities and constraints; and (6) agreement on the goals of sustainable forestry. A diversity of products and markets builds a more resilient forest-based economy by mitigating impacts of disruptions in any individual market, adding value to biomass, increasing employment, and reducing forest risks to fire, insects, and disease.

Bioenergy↗

Improving the short-wave infrared response of strained GeSn/Ge multiple quantum wells by rapid thermal annealing

In this work, the evolution of structural, optical and optoelectronic properties of coherently strained Ge 0.883 Sn 0.117 /Ge multiple quantum wells (MQWs) grown by molecular beam epitaxy under rapid thermal annealing (RTA) is systematically investigated. The MQW structure remains fully-strained state with RTA at 400 °C or below and disrupts at higher annealing temperatures due to Sn segregation and interdiffusion of Ge and Sn atoms. The GeSn well layers exhibit the strongest absorption in 2.0–2.4 μm after annealing at 400 °C and become transparent above 1.8 μm after RTA at 600 °C or beyond due to serve Sn segregation. Owing to improved crystal quality after RTA at 400 °C, the dark current of the fabricated metal-semiconductor-metal photodetector is effectively lowered by more than two times. Additionally, the responsivities at 1.55 and 2.0 μm are improved by 4.15 and 3.78 folds, respectively, compared to those of the as-grown sample. Here, the results can be an insightful guidance for the development of high-performance short-wave infrared photonic devices based on Sn-containing group-IV low-dimensional structures.

36 MATERIALS SCIENCE↗

Comparing (stochastic-selection) ab initio multiple spawning with trajectory surface hopping for the photodynamics of cyclopropanone, fulvene, and dithiane

Ab Initio Multiple Spawning (AIMS) simulates the excited-state dynamics of molecular systems by representing nuclear wavepackets in a basis of coupled traveling Gaussian functions, called trajectory basis functions (TBFs). New TBFs are spawned when nuclear wavepackets enter regions of strong nonadiabaticity, permitting the description of non-Born–Oppenheimer processes. The spawning algorithm is simultaneously the blessing and the curse of the AIMS method: it allows for an accurate description of the transfer of nuclear amplitude between different electronic states, but it also dramatically increases the computational cost of the AIMS dynamics as all TBFs are coupled. Recently, a strategy coined stochastic-selection AIMS (SSAIMS) was devised to limit the ever-growing number of TBFs and tested on simple molecules. In this work, we use the photodynamics of three different molecules—cyclopropanone, fulvene, and 1,2-dithiane—to investigate (i) the potential of SSAIMS to reproduce reference AIMS results for challenging nonadiabatic dynamics, (ii) the compromise achieved by SSAIMS in obtaining accurate results while using the smallest average number of TBFs as possible, and (iii) the performance of SSAIMS in comparison to the mixed quantum/classical method trajectory surface hopping (TSH)—both in terms of its accuracy and computational cost. We show that SSAIMS can accurately reproduce the AIMS results for the three molecules considered at a much cheaper computational cost, often close to that of TSH. We deduce from these tests that an overlap-based criterion for the stochastic-selection process leads to the best agreement with the reference AIMS dynamics for the smallest average number of TBFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗