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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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Multipurpose cable with an integral thermocouple circuit measures strain, vibration, pressure, throughout a wide temperature range. This cable reduces bulky and complex circuitry by eliminating separate thermocouples for each transducer.
System consists of digital voltmeter with binary coded decimal output, programmer, multiplexer, and two to six gated digital displays. Maximum number of circuits monitored is determined by digital voltmeter, rate of change of parameter being measured and complexity of multiplexer design.
Five megahertz RF (radiofrequency) signal attenuator utilizing RF quadrature hybrid, and optically viable-resistance load controlled by lamp circuit exhibits little phase shift. Circuit is designed to help distribute standard RF signal of controlled amplitude, and phase throughout complex of facilities could be useful in application to precision test equipment and communication electronics.
Models for the analysis of photovoltaic (PV) systems' designs, implementation policies, and economic performance, have proliferated while keeping pace with rapid changes in basic PV technology and extensive empirical data compiled for such systems' performance. Attention is presently given to the results of a comparative assessment of ten well documented and widely used models, which range in complexity from first-order approximations of PV system performance to in-depth, circuit-level characterizations. The comparisons were made on the basis of the performance of their subsystem, as well as system, elements. The models fall into three categories in light of their degree of aggregation into subsystems: (1) simplified models for first-order calculation of system performance, with easily met input requirements but limited capability to address more than a small variety of design considerations; (2) models simulating PV systems in greater detail, encompassing types primarily intended for either concentrator-incorporating or flat plate collector PV systems; and (3) models not specifically designed for PV system performance modeling, but applicable to aspects of electrical system design. Models ignoring subsystem failure or degradation are noted to exclude operating and maintenance characteristics as well.
Technical memorandum presents collection of software packages in Ada implementing mathematical functions used in science and engineering. Provides programmer with function support in Pascal and FORTRAN, plus support for extended-precision arithmetic and complex arithmetic. Valuable for testing new computers, writing computer code, or developing new computer integrated circuits.
An improved approach to the mathematical modeling of feedback control of thermal networks has been devised. Heretofore software for feedback control of thermal networks has been developed by time-consuming trial-and-error methods that depend on engineers expertise. In contrast, the present approach is a systematic means of developing algorithms for feedback control that is optimal in the sense that it combines performance with low cost of implementation. An additional advantage of the present approach is that a thermal engineer need not be expert in control theory. Thermal networks are lumped-parameter approximations used to represent complex thermal systems. Thermal networks are closely related to electrical networks commonly represented by lumped-parameter circuit diagrams. Like such electrical circuits, thermal networks are mathematically modeled by systems of differential-algebraic equations (DAEs) that is, ordinary differential equations subject to a set of algebraic constraints. In the present approach, emphasis is placed on applications in which thermal networks are subject to constant disturbances and, therefore, integral control action is necessary to obtain steady-state responses. The mathematical development of the present approach begins with the derivation of optimal integral-control laws via minimization of an appropriate cost functional that involves augmented state vectors. Subsequently, classical variational arguments provide optimality conditions in the form of the Hamiltonian equations for the standard linear-quadratic-regulator (LQR) problem. These equations are reduced to an algebraic Riccati equation (ARE) with respect to the augmented state vector. The solution of the ARE leads to the direct computation of the optimal proportional- and integral-feedback control gains. In cases of very complex networks, large numbers of state variables make it difficult to implement optimal controllers in the manner described in the preceding paragraph.
Abstract Dynamic simulation of materials is a promising application for near-term quantum computers. Current algorithms for Hamiltonian simulation, however, produce circuits that grow in depth with increasing simulation time, limiting feasible simulations to short-time dynamics. Here, we present a method for generating circuits that are constant in depth with increasing simulation time for a specific subset of one-dimensional (1D) materials Hamiltonians, thereby enabling simulations out to arbitrarily long times. Furthermore, by removing the effective limit on the number of feasibly simulatable time-steps, the constant-depth circuits enable Trotter error to be made negligibly small by allowing simulations to be broken into arbitrarily many time-steps. For an N -spin system, the constant-depth circuit contains only $\mathcal {O}(N^{2})$ O ( N 2 ) CNOT gates. Such compact circuits enable us to successfully execute long-time dynamic simulation of ubiquitous models, such as the transverse field Ising and XY models, on current quantum hardware for systems of up to 5 qubits without the need for complex error mitigation techniques. Aside from enabling long-time dynamic simulations with minimal Trotter error for a specific subset of 1D Hamiltonians, our constant-depth circuits can advance materials simulations on quantum computers more broadly in a number of indirect ways.
Signaling cascades are crucial for transducing stimuli in biological systems, enabling multiple stimuli to regulate a downstream target with precisely controlled timing and amplifying signals through a series of intermediary reactions. Developing a robust signaling system with such capabilities would be pivotal for programming complex behaviors in synthetic DNA-based molecular devices. However, although “software” such as nucleic acid circuits could potentially be harnessed to relay signals to DNA-based nanostructure hardware, such explorations have been limited. Here, in this study, we develop a platform for transducing a variety of stimuli via messenger-mediated reactions to regulate the release and reloading of gold nanoparticles (AuNPs) in a 3D DNA framework. In the first step, an in vitro transcription circuit is engineered to sense and amplify chemical stimuli, including arbitrary DNA sequences and proteins, producing RNA. In the second step, the RNA releases the DNA-coated AuNPs from the DNA framework via a strand displacement reaction. AuNP reloading is controlled by a separate step driven by degradation of the RNA. Our platform holds promise for applications requiring dynamic multiagent control over DNA-based devices, offering a versatile tool for advanced molecular device engineering.
Generating high-fidelity, tunable entanglement between qubits is crucial for realizing gate-based quantum computation. In superconducting circuits, tunable interactions are often implemented using flux-tunable qubits or coupling elements, adding control complexity and noise sources. Here, we realize a tunable $ZZ$ interaction between two transmon qubits with fixed frequencies and fixed coupling, induced by driving both transmons off-resonantly. We show tunable coupling over one order of magnitude larger than the static coupling, and change the sign of the interaction, enabling cancellation of the idle coupling. Further, this interaction is amenable to large quantum processors: the drive frequency can be flexibly chosen to avoid spurious transitions, and because both transmons are driven, it is resilient to microwave crosstalk. We apply this interaction to implement a controlled phase (CZ) gate with a gate fidelity of $99.43(1)\%$ as measured by cycle benchmarking, and we observe the fidelity is limited by incoherent errors.
In grids with large penetration of converterinterfaced resources (CIRs), measurements of voltage, current, and line parameters can fluctuate significantly during fault conditions. These fluctuations, combined with complex network topologies and extensive system branching, make accurate fault location challenging. Faults, such as short circuits, can cause prolonged outages with serious socio-economic impacts, highlighting the need for rapid fault identification to minimize downtime. However, current fault detection methods—such as relays and digital fault recorders—often relay information too slowly, impeding swift corrective action. Given the limited availability of high-resolution phasor measurement units, this paper introduces an optimization-based observer to estimate fault locations, grid line parameters, and voltages using local CIR measurements. To preserve the confidentiality of CIRs and enhance estimation accuracy, this study uses a black-box model of CIRs. This bottom-up, event-driven approach can enhances protection and control systems through optimized and real-time fault detection. Simulation results show that the optimization-based data-driven observer can accurately detect fault locations and estimate grid states and parameters, providing valuable insights for utilities and operators in grid applications.
The volume examines the scientific interfaces and technological applications of physics. Twelve areas are dealt with: biological physics-biophysics, the brain, and theoretical biology; the physics-chemistry interface-instrumentation, surfaces, neutron and synchrotron radiation, polymers, organic electronic materials; materials science; geophysics-tectonics, the atmosphere and oceans, planets, drilling and seismic exploration, and remote sensing; computational physics-complex systems and applications in basic research; mathematics-field theory and chaos; microelectronics-integrated circuits, miniaturization, future trends; optical information technologies-fiber optics and photonics; instrumentation; physics applications to energy needs and the environment; national security-devices, weapons, and arms control; medical physics-radiology, ultrasonics, MNR, and photonics. An executive summary and many chapters contain recommendations regarding funding, education, industry participation, small-group university research and large facility programs, government agency programs, and computer database needs.
A water tunnel facility at the NASA Dryden Flight Research Facility is described. This water tunnel facility, the Flow Visualization Facility, is used primarily for visualizing and analyzing vortical flows on aircraft models and other shapes at high incidence angles. The tunnel is used extensively as a low cost diagnostic tool to help understand complex flows over aircraft and other full scale vehicles. The facility consists primarily of a closed circuit water tunnel with a 16 in by 24 in vertical test section. The velocity of the flow through the test section can be varied from 0 to 10 in/sec, however 3 in/sec has been found to be optimum for flow visualization. This corresponds to a unit Reynolds number of 23,000 per foot and a turbulence level over the majority of the test section below .05%. Flow visualization techniques described include the dye tracer, laser light sheet and the shadowgraph techniques. Limited correlation to full-scale flight data is shown.
Continuing on the successful progress of NIAC (NASA Innovative Advanced Concepts) Phase I, this report summarizes the technical progress achieved under NIAC Phase II during the performance period September 19, 2014 to June 18, 2017. During this period, the research team has made the following accomplishments: designed and layout a silica photonic integrated circuit (PIC) as a two baselineinterferometric imager; constructed an experiment to utilize the two baselines for complex visibility measurementon a point source and a variable width slit; analyzed and studied the testbed results (in collaboration with Lockheed Martin); designed and layout Si3N4 PICs for the low-resolution and high-resolution SPIDER (Segmented Planar Imaging Detector for Electro-Optical Reconnaissance) telescope; fabricated the multi-layer Si3N4 PIC for low and high resolution SPIDER telescope; characterized the optical throughput and heater response for Si3N4 PIC for low and highresolution SPIDER telescopes; carried out imaging experiments using the Si3N4 PIC low-resolution version (in collaboration with Lockheed Martin); investigated signal-to-noise (SNR) ratio of SPIDER imager compared to the conventional panchromatic imager (in collaboration with Lockheed Martin); fulfilled the SNR simulation upon SPIDER imager (in collaboration with Lockheed Martin).
Recently, the problem of compiling general quantum algorithms for implementation on near-term quantum processors has been introduced to the AI community. Previous work demonstrated that temporal planning is an attractive approach for part of this compilation task, specifically, the routing of circuits that implement the Quantum Alternating Operator Ansatz (QAOA) applied to theMaxCut problem on a quantum processor architecture. In this paper, we extend the earlier work to route circuits that implement QAOAfor Graph Coloring problems. QAOA for coloring requires execution of more, and more complex, operations on the chip, which makes routing a more challenging problem. We evaluate the approach on state-of-the-art hardware architectures from leading quantum computing companies. Additionally, we investigate applying the planning approach to qubit initialization as well as routing. Our empirical evaluation shows that temporal planning compares well to reasonable analytic upper bounds [20], and that solving qubit initialization with a classical planner generally helps temporal planners in finding shorter-makespan compilations for QAOA for Graph Coloring.These advances suggest that temporal planning can be an effective approach for more complex quantum computing algorithms and architectures.
A high-power pulsed surface processing system includes insulated-gate bipolar transistors (IGBT) to replicate desirable pulse structures with high precision, at low cost, and with high reliability within a single system. The pulsed surface processing system includes a power supply, an anode and a cathode, a dual gate driver supplying power to one or more IGBT gates, and one or more capacitor banks. Pulse formation software controls the timing and duration of electrical pulses to the electrodes. A freewheeling diode protects the system from an abrupt reduction of current in the circuit. The high-power pulsed surface processing system may be used to control versatile and complex pulse structures while with precise control of instantaneous pulse powers, pulse timing, and process control. The inclusion of dual gate drivers also offers the ability for multiple pulsers to be created and “slaved” together for a wide variety of custom processes.
A goal of connectomics is to reveal the links between neural circuits and behavior. Larvae of the primitive chordateCionaare well-suited to make contributions in this area. In addition to having a described connectome,Cionalarvae have a range of readily-quantified behaviors. Moreover, the small number of neurons in the larval CNS (∼180) holds the promise of a comprehensive characterization of individual neurons. We present single-neuron predictions for glutamate receptor (GlutR) expression based onin situhybridization. Included are both ionotropic receptors (AMPA, NMDA, and Kainate), and metabotropic receptors. The predicted glutamate receptor expression dataset is discussed in the context of known circuits driving behaviors such as phototaxis, mechanosensation, and looming shadow response. The predicted expression of AMPA and NMDA receptors may help to resolve issues regarding the co-production of GABA and glutamate by a subset of photoreceptors. The targets of these photoreceptors in the midbrain appear to express NMDA receptors, but not AMPA receptors. This is in agreement with previous results indicating that GABA is the primary neurotransmitter from the photoreceptors evoking a swimming response through a disinhibition mechanism, and that glutamate may, therefore, have only a modulatory action in this circuit. Other findings reported here are more unexpected. For example, many of the targets of glutamatergic epidermal sensory neurons (ESNs) do not express any of the ionotropic receptors, yet the ESNs themselves express metabotropic receptors. Thus, we speculate that their production of glutamate may be for communication with neighboring ESNs, rather than to their interneuron targets. Significance StatementSimple invertebrates offer a tractable alternative to complex vertebrate brains, facilitating holistic understanding of brain function. One such invertebrate is the marine chordateCiona, which has the benefit of a complete synaptic wiring diagram for its swimming larva. This “connectome” allowed identification of putative neural circuits driving defined behaviors. Fuller understanding of neural circuits, however, requires a description of the attributes of individual neurons. This study focuses on the excitatory neurotransmitter glutamate, which signals via a complex set of both ionotropic and metabotropic receptors. Here, we present a nervous system-wide prediction of GlutR expression inCionaat the individual neuron level, considered in the context of neural circuits, with emphasis on how GlutR expression accounts for function of neural circuits.
Algorithms that search for a pattern within a larger data-set appear ubiquitously in text and image processing. Here, we present an explicit, circuit-level implementation of a quantum pattern-matching algorithm that matches a search string (pattern) of length M inside a longer text of length N. Our algorithm has a time complexity of $\tildeO$($\sqrt{N}$), while the space complexity remains modest at O(N+ M). We report the quantum gate counts relevant for both pre-fault-tolerant and fault-tolerant regimes.
The accurate simulation of cold-test results including dispersion, on-axis beam interaction impedance, and attenuation of a helix traveling-wave tube (TWT) slow-wave circuit using the three-dimensional code MAFIA (Maxwell's Equations Solved by the Finite Integration Algorithm) was demonstrated for the first time. Obtaining these results is a critical step in the design of TWT's. A well-established procedure to acquire these parameters is to actually build and test a model or a scale model of the circuit. However, this procedure is time-consuming and expensive, and it limits freedom to examine new variations to the basic circuit. These limitations make the need for computational methods crucial since they can lower costs, reduce tube development time, and lessen limitations on novel designs. Computer simulation has been used to accurately obtain cold-test parameters for several slow-wave circuits. Although the helix slow-wave circuit remains the mainstay of the TWT industry because of its exceptionally wide bandwidth, until recently it has been impossible to accurately analyze a helical TWT using its exact dimensions because of the complexity of its geometrical structure. A new computer modeling technique developed at the NASA Lewis Research Center overcomes these difficulties. The MAFIA three-dimensional mesh for a C-band helix slow-wave circuit is shown.