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This whitepaper provides details for the background, conventions, definitions, transformation equations, examples, and implementation used in the Solid Body Geometry (SBG) transformations in Monte Carlo Application ToolKit (MCATK).
In order to improve their long-term viability, wave energy converters (WECs) need to be able to shed loads when a threshold wave condition is exceeded. As shown by Tom et al. (2016) [1], provision of adjustable flaps within the body of an oscillating surge wave energy converter (OSWEC) allows wave energy to pass through the device. A control system may then be able to open and close the flaps when waves approaching the device exceed preset thresholds. The variable-geometry OSWEC (VG-OSWEC) concept studied in this paper is a bottom-hinged, rectangular wave paddle with five flaps of elliptical cross-section embedded into the face of the paddle. System ID tests were conducted on this VG-OSWEC device at a 1:14 scale in a wave basin. Free decay tests showed that the damping was distinctly nonlinear when the flaps were fully open, and the natural frequency increased by 40% when compared with the flaps in a fully closed configuration. Tests with regular wave conditions were used to develop the response amplitude operator for the rotational motion about the hinge. These response amplitude operator results when compared with numerical simulations run using WEC-Sim/WAMIT and ANSYS AQWA, show strong agreement with the flap open and closed conditions. The regular-wave condition measurements also show that the wave excitation moment about the hinge was reduced by up to 60% when the flaps were fully open. The experiments serve to demonstrate the potential of the variable geometry design to shed loads and survive harsh ocean environments.
This research presents the first results from a new Rotating Detonation Combustor (RDC) design with an axial air inlet and rear-facing angled fuel injection. This design features a variable air inlet that allows for the study of the effect of inlet area ratio on operation and to directly study the coupling between the air plenum and channel of the RDC while minimizing inlet pressure losses. This device maintains the same downstream channel configuration as those previously tested in our laboratory, which includes a 154 mm outer channel diameter and a constant area channel with a width of 7.6 mm. All tests were completed with a downstream hydrogen-air afterburner capable of flashing back in the channel to initiate detonation operation. Initial tests demonstrated successful operation at air mass flow rates from 160 to 770 g/s and equivalence ratios from 0.53 to 1.05 at multiple air inlet to channel area ratios, indicated that sensors installed within the air feed plenum are able to characterize the dynamic characteristics of waves within the detonation channel, and verified that the design goals for this configuration were achieved.
We study the renormalization group (RG) running of the nonsinglet tensor operator, for N f = 3 QCD with Wilson fermions in a mixed action setup, with standard Schrödinger functional (SF) boundary conditions for sea quarks and chirally rotated Schrödinger functional ( χ SF ) boundary conditions for valence quarks. Based on a recursive finite-size scaling technique we compute nonperturbatively the tensor step-scaling function for an energy range between a hadronic scale and an electroweak scale, above which perturbation theory may be safely applied. Our result is expressed as the RG-running factor T RGI / [ T ( μ had ) ] R , where the numerator is the scale independent (renormalization group invariant—RGI) tensor operator and the denominator is its renormalized counterpart at a hadronic scale μ had = 233 ( 8 ) MeV in a given scheme. We determine the step-scaling function in four distinct renormalization schemes. We also compute the renormalization parameters of these schemes at μ had which, combined with the RG-running factor, gives the scheme-independent quantity Z T RGI ( g 0 2 ) in four schemes and for a range of bare gauge couplings in which large volume hadronic matrix element simulations are performed by the CLS consortium in N f = 2 + 1 QCD. All four results are compatible and also agree with a recent determination based on a unitary setup for Wilson quarks with Schrödinger functional boundary conditions [arXiv:2309.04314]. This provides a strong universality test. Published by the American Physical Society 2024
Here, we investigate optimized quantum state preparation for quantum metrology applications in noisy environments. Using the QFI-OPT package, we simulate a low-depth variational quantum circuit (VQC) composed of a sequence of global rotations and entangling operations applied to a chain of qubits that are subject to dephasing noise. The parameters controlling the VQC are numerically optimized to maximize the quantum Fisher information, which characterizes the ultimate metrological sensitivity of a quantum state with respect to a global rotation. We find that, regardless of the details of the entangling operation implemented in the VQC, the optimal quantum states can be broadly classified into a trio of qualitative regimes, i.e., catlike, squeezed like, and product states, associated with different dephasing rates. Our findings are relevant for designing optimal state-preparation strategies for next-generation quantum sensors exploiting entanglement, such as time and frequency standards and magnetometers, aimed at achieving state-of-the-art performance in the presence of noise and decoherence.
This report determines local truncation errors for common stress integration algorithms used in explicit finite element codes with hypoelastic material models. The hypoelastic integration algorithms in question utilize an operator splitting procedure in a rotation neutralized configuration, where the stress response is determined from de- coupling the total deformation into rotational and strain dependent components. This document analyzes the error in evolving the stress given a one-step time increment Δt and compares the errors associated with both the rotational and strain components of the operator splitting method. A slight modification to a traditional algorithm is proposed and studied, where the rate of deformation is appropriately rotated from the midstep configuration at t n+1/2 to the end step configuration at t n+1 before the constitutive evaluation. The proposed modification either completely eliminates the error associated with the rotation rate or is of the same order of magnitude as the original algorithm for the three test cases considered in this report. These cases consist of an unaxial stretch with a constant true strain rate with a rigid body rotation, an uniaxial stretch with a constant engineering strain rate with a rigid body rotation, and a simple shear deformation. All three cases are compared to a closed form solution, and in almost every test case the alternative algorithm yields the most accurate one-step local truncation error.
As the operational time window of experimental rotating detonation engines (RDEs) is expanded and the technology matures toward integration within gas turbines, monitoring techniques must evolve to offer computationally efficient and highly time-resolved diagnostics. In this study, computer vision object detection methodology that seeks to reduce data processing time and calculate wave velocity within drastically reduced time intervals as compared to traditional high-frame-rate RDE images analysis techniques is proposed. The adapted you-only-look-once object detection network is trained to detect individual detonation waves within single down-axis RDE images. The wave location and rotational direction detected within a frame are tracked through a series of high-speed images to calculate the frame-to-frame wave velocity with the time-step resolution of $\mathrm{20 μs}$ across a series of frames. The analysis of the annotation box size and image linearization effects is presented, demonstrating the lowest frame-to-frame velocity total uncertainty of $\mathrm{±3.8\%}$ and the highest classification speed of 9.5 frames per second using linearized images. Linearized images “unwrap” the RDE annulus pixel region to a reduced image size. Here, this new method offers great reductions in data processing times and unsteady detonation behavior insight at intervals more comparable to the timescales of detonation wave interactions via the application of machine learning to experimental RDE data.
Abstract In the turbine section of a modern gas turbine engine, components exposed to the main gas path flow rely on cooling air to maintain hardware durability targets. Therefore, monitoring turbine cooling flow is essential to the diagnostic and prognostic efficacy of a condition-based operation and maintenance (CBOM) approach. This study supports CBOM goals by leveraging supervised machine learning to estimate relative changes to local film-cooling flowrate using surface temperature measured on the pressure side of a rotating turbine blade operating at engine-relevant aerothermal conditions. Throughout the lifetime of a film-cooled turbine component, characteristics of the film-cooling flow—such as film trajectory and cooling effectiveness—vary as degradation-driven geometry distortions occur, which ultimately affects the relationship between the model input and the model output—film-cooling flowrate predictions. The present study addresses this complication by testing a data-driven model on multiple turbine blades of the same nominal design, but with each blade exhibiting different localized film-cooling flow characteristics. By testing the model in this manner, strategies for mitigating the detrimental effects of film-cooling flow characteristic variations on model performance were investigated, and the corresponding flowrate prediction accuracy was quantified.
Abstract With climate change, heat waves have become more frequent and intense. Rotating power outages happen when the power supply is unable to meet the cooling demand increase resulting from extreme high temperatures. Power outages during heat waves expose residents to high risks of overheating. In this study, we propose a novel data-driven inverse modelling approach to inform decision makers and grid operators on planning rotating power outages. We first infer the building thermal characteristics using the connected smart thermostat data, and used the estimated thermal dynamics to simulate the thermal resilience during a heat wave event. Our proposed method was tested for the California power outage in August 2020 by using the open source Ecobee Donate Your Data dataset. We found in California the power outage should not last more than two hours during heat waves to avoid overheating risks. Informing the residents in advance so they can prepare for it through pre-cooling is a simple but effective strategy to expand the acceptable power outage duration. In addition to assisting power outage planning, the proposed method can be used for other applications, such as to evaluate a building energy efficiency policy, to examine fuel poverty, and to estimate the load shifting potential of building stocks.
. In order to maintain viability as a future power-generating technology, concentrating solar power (CSP) must reduce its levelized cost of electricity (LCOE). One component of solving this problem is reducing the cost of the power block while simultaneously increasing the efficiency of the thermodynamic cycle. One disruptive technology that has the promise to accomplish this is supercritical CO2 based power cycles. These cycles are conceptually similar to steam cycles; however, they have substantially smaller turbomachinery at equivalent power while also delivering more efficiency at turbine inlet temperatures of 500-700 degrees Celsius. This paper will summarize the current status of a US Department of Energy project to develop machinery to support a 10 MW sCO2 power cycle. The team of Southwest Research Institute® (SwRI®) and Hanwha Power Systems America, proposed to develop an integrally-geared (IG) compressor-expander (compander) for use in a nominal 10 MW-scale concentrated solar power (CSP) supercritical carbon dioxide (sCO2) plant application. This integrally-geared compander (IGC) comprises multiple pinion shafts interconnected on a single bull gear to create a compact package, and utilizes a low-cost, low-speed driver. In addition, the integrally geared architecture allows each pinion to operate at different rotational speeds to optimize performance and easily allow for inter-stage cooling and turbine re-heat to further enhance both stage and cycle efficiency. The close integration of all turbomachinery elements into a single integrally-geared (IG) machine creates a design that lends itself to power block modularization, which makes it suitable for waste heat recovery, fossil fuel power plants, and especially CSP applications. As part of the commercialization of this technology, it is necessary to reduce risk by validation testing of key components. In the current work, the focus is developing a test loop to enable safe testing of the main compressor stage across a wide range of operating conditions, and to validate the mechanical integrity of the turbine at full pressure, temperature, and speed. Developing a test loop for sCO2 requires balancing a number of design alternatives that impact cost, lead time, safety, and performance. The current work discusses the design process for the reduced flow test loop for the compander, and supporting documentation supporting the viability of the test loop
Quantum signal processing (QSP) and quantum singular value transformation (QSVT) currently stand as the most efficient techniques for implementing functions of block-encoded matrices, a central task that lies at the heart of most prominent quantum algorithms. However, current QSP approaches face several challenges, such as the restrictions imposed on the family of achievable polynomials and the difficulty of calculating the required phase angles for specific transformations. In this paper, we present a generalized quantum signal processing (GQSP) approach, employing general SU(2) rotations as our signal-processing operators, rather than relying solely on rotations in a single basis. Our approach lifts all practical restrictions on the family of achievable transformations, with the sole remaining condition being that | P | ≤ 1 , a restriction necessary due to the unitary nature of quantum computation. Furthermore, GQSP provides a straightforward recursive formula for determining the rotation angles needed to construct the polynomials in cases where P and Q are known. In cases where only P is known, we provide an efficient optimization algorithm capable of identifying in under a minute of GPU time, a corresponding Q for polynomials of degree on the order of 10 7 . We further illustrate GQSP simplifies QSP-based strategies for Hamiltonian simulation, offer an optimal solution to the ϵ -approximate fractional query problem that requires O ( ( 1 / δ ) + log ( 1 / ϵ ) ) queries to perform where O ( 1 / δ ) is a proved lower bound, and introduces novel approaches for implementing bosonic operators. Moreover, we propose a novel framework for the implementation of normal matrices, demonstrating its applicability through synthesis of diagonal matrices, as well as the development of a new algorithm for convolution through synthesis of circulant matrices using only O ( d log N + log 2 N ) 1 and 2-qubit gates for a filter of lengths d . Published by the American Physical Society 2024
Fast scramblers are dynamical quantum systems that produce many-body entanglement on a timescale that grows logarithmically with the system size N. Here, we propose and investigate a family of deterministic, fast scrambling quantum circuits realizable in near-term experiments with arrays of neutral atoms. We show that three experimental tools—nearest-neighbor Rydberg interactions, global single-qubit rotations, and shuffling operations facilitated by an auxiliary tweezer array—are sufficient to generate nonlocal interaction graphs capable of scrambling quantum information using only O(logN) parallel applications of nearest-neighbor gates. These tools enable direct experimental access to fast scrambling dynamics in a highly controlled and programmable way and can be harnessed to produce highly entangled states with varied applications.
This Fortran code consists of multiple modules with a focus on simplifying array operations, image processing, and numerical computation especially for computational geophysics applications. We intend to use this code to demonstrate the application and usefulness of Fortran interface and templates for generic programming, especially for computational geophysics and seismology applications. The code has several notable features. Firstly, it is based on a modularized structure, where each module contains multiple functions but with a focus of functionality. Secondly, it heavily uses interfaces and templates for improving the genericness and convenience of the resulting code, where a same function interface can enclose a group of functions that perform the same functionality but with inputs/output variables of different data types. Thirdly, it includes a variety of generic functions with an emphasis on array operations, such as rotation, flipping, cropping, padding, fast Fourier transform, Gaussian blurring, interpolation, and so on. We name this package FLIP – a generic Fortran Library based on Interfaces and Templates.
Nuclear thermal propulsion is currently being developed for manned Mars and Lunar missions by the National Aeronautics and Space Administration due to its increased specific impulse and significant thrust to reduce the total trip time and cost of deep space missions. To maximize the performance of the engine the exit hydrogen propellant temperature should, ideally, be uniformly distributed among all the fuel elements. Uniform exit temperatures imply that the power must be flattened as much as possible. This paper leverages decoupled neutronic and thermal-hydraulic models to assess the thermal performance and reactivity tradeoffs associated with flattening the radial power distribution by adjusting the fuel kernel loading for each fuel element within the core. The results suggest that a uniform radial power distribution for a single control drum position will not necessarily yield an optimal core design due to the higher variance in power and thus maximum fuel and exit propellant temperature as the control drums rotate out during operation. The results presented here only point to the design characteristics be considered when core-level multi-physics simulations are applied in the context of a specific mission. (authors)
Sequences B, C, and D: Downwind Baseline (F), Downwind Low Pitch (F), Downwind High Pitch (F) This test sequence used a downwind, teetered turbine with a 3.4° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of ±180° were achieved at low wind speeds, and yaw angles of -20° to 10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence B, 0° for sequence C, and 6° for sequence D. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected.
Sequences B, C, and D: Downwind Baseline (F), Downwind Low Pitch (F), Downwind High Pitch (F) This test sequence used a downwind, teetered turbine with a 3.4° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of ±180° were achieved at low wind speeds, and yaw angles of -20° to 10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence B, 0° for sequence C, and 6° for sequence D. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected.
Sequences B, C, and D: Downwind Baseline (F), Downwind Low Pitch (F), Downwind High Pitch (F) This test sequence used a downwind, teetered turbine with a 3.4° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of ±180° were achieved at low wind speeds, and yaw angles of -20° to 10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence B, 0° for sequence C, and 6° for sequence D. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected.
Sequences H, I, and J: Upwind Baseline (F), Upwind Low Pitch (F), Upwind High Pitch (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of –30 to 180° were achieved at low wind speeds, and angles of ±10° were achieved for high wind speeds. The blade tip pitch was 3° for sequence H, 0° for sequence I, and 6° for sequence J. These three sequences were interleaved during testing because the pitch angle change was easily made by the turbine operator. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pretensioned to 40,000 N. In addition to the standard 30-second campaigns, yaw sweeps were done at 7 m/s and 10 m/s. These 6-minute campaigns were collected while the yaw drive rotated the turbine 360° at a rate of 1°/s. The file names for these campaigns use the letter designation, followed by two digits for wind speed, followed by YS, followed by 000.