An Electric Vehicle Routing Optimization Model With Hybrid Plug-In and Wireless Charging Systems
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42 ENGINEERING↗
SEARCH · Engineering Papers
Results for “linear optimization”
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Physics-Informed CoKriging: A Gaussian-Process-Regression-Based Multifidelity Method for Data-Model Convergence
In this work, we propose a new Gaussian process regression (GPR)-based multifidelity method: physics-informed CoKriging (CoPhIK). In CoKriging-based multifidelity methods, the quantities of interest are modeled as linear combinations of multiple parameterized stationary Gaussian processes (GPs), and the hyperparameters of these GPs are estimated from data via optimization. In CoPhIK, we construct a GP representing low-fidelity data using physics-informed Kriging (PhIK), and model the discrepancy between low- and highfidelity data using a parameterized GP with hyperparameters identified via optimization. Our approach reduces the cost of optimization for inferring hyperparameters by incorporating partial physical knowledge. We prove that the physical constraints in the form of deterministic linear operators are satisfied up to an error bound. Furthermore, we combine CoPhIK with a greedy active learning algorithm for guiding the selection of additional observation locations. The eciency and accuracy of CoPhIK are demonstrated for reconstructing the partially observed modified Branin function, reconstructing the sparsely observed state of a steady state heat transport problem, and learning a conservative tracer distribution from sparse tracer concentration measurements.
Yang, Xiu↗
A greedy Galerkin method to efficiently select sensors for linear dynamical systems
A key challenge in inverse problems is the selection of sensors to gather the most effective data. In this paper, we consider the problem of inferring the initial condition to a linear dynamical system and develop an efficient control-theoretical approach for greedily selecting sensors. Our method employs a Galerkin projection to reduce the size of the inverse problem, resulting in a computationally efficient algorithm for sensor selection. As a byproduct of our algorithm, we obtain a preconditioner for the inverse problem that enables the rapid recovery of the initial condition. Here, we analyze the theoretical performance of our greedy sensor selection algorithm as well as the performance of the associated preconditioner. Finally, we verify our theoretical results on various inverse problems involving partial differential equations.
97 MATHEMATICS AND COMPUTING↗
A prototype hybrid mode cavity for heterodyne axion detection
In the heterodyne approach to axion detection, axion dark matter induces transitions between two modes of a microwave cavity, resulting in a parametrically enhanced signal power. We describe the fabrication and characterization of a prototype normal conducting cavity specifically optimized for heterodyne detection. Corrugations on the cavity walls support linearly polarized hybrid modes which maximize the signal power while strongly suppressing noise. We demonstrate tuning mechanisms which allow one mode frequency to be scanned across a 4 MHz range, while suppressing cross-coupling noise by at least 80 dB. A future superconducting cavity with identical geometry to our prototype would have the potential to probe orders of magnitude beyond astrophysical bounds.
Li, Zenghai [SLAC]↗
Aperture‐Synthesis Radar Imaging With Compressive Sensing for Ionospheric Research
Abstract Inverse methods involving compressive sensing are tested in the application of two‐dimensional aperture‐synthesis imaging of radar backscatter from field‐aligned plasma density irregularities in the ionosphere. We consider basis pursuit denoising, implemented with the fast iterative shrinkage thresholding algorithm, and orthogonal matching pursuit (OMP) with a wavelet basis in the evaluation. These methods are compared with two more conventional optimization methods rooted in entropy maximization (MaxENT) and adaptive beamforming (linearly constrained minimum variance or often “Capon's Method.”) Synthetic data corresponding to an extended ionospheric radar target are considered. We find that MaxENT outperforms the other methods in terms of its ability to recover imagery of an extended target with broad dynamic range. Fast iterative shrinkage thresholding algorithm performs reasonably well but does not reproduce the full dynamic range of the target. It is also the most computationally expensive of the methods tested. OMP is very fast computationally but prone to a high degree of clutter in this application. We also point out that the formulation of MaxENT used here is very similar to OMP in some respects, the difference being that the former reconstructs the logarithm of the image rather than the image itself from basis vectors extracted from the observation matrix. MaxENT could in that regard be considered a form of compressive sensing.
Hysell, D. L.↗
Flexible organic integrated electronics for self-powered multiplexed ocular monitoring
Smart contact lens has drawn extensive research interests due to the noninvasive real-time detection of the human body to provide biomedical information for health management. However, it has been difficult to accurately measure the physiological signals in tears, and the use of external power source has also hindered the future applications. Here, we demonstrated an organic electrochemical transistor based multiplexed sensors self-powered by the organic solar cells (OSCs). The integrated device was fabricated via simple process including solution blade-coating and thermal evaporation. OSCs were optimized to provide optimal operation voltage for the sensors that exhibit semilog-linear response to the glucose and calcium ions in tear fluids without any peripheral circuits. The sensing signals can be transmitted to the laptop wirelessly through a near filed communication unit. This integrated self-powered multiplexed sensing device will provide real-time monitoring of the biomarkers in tears, prospected to be installed on the smart contact lens for the early detection and diagnosis of diabetes.
36 MATERIALS SCIENCE↗
Flux-pumped impedance-engineered broadband Josephson parametric amplifier
Broadband quantum-limited amplifiers play a critical role in the single-shot readout of superconducting qubits, but a popular implementation, the traveling wave parametric amplifier, involves a complex design and fabrication process. Here, we present a simple design for a Josephson parametric amplifier, using a lumped element resonator comprising a superconducting quantum interference device whose useful bandwidth is enhanced with an on-chip impedance-matching circuit. Additionally, we demonstrate a flux-coupling geometry that maximizes the coupling to the Josepson loop and minimizes spurious excitation of the amplifier resonant circuit. The amplifier, which operates in a flux-pumped mode, is demonstrated with a power gain of more than 20dB over a bandwidth of about 300MHz, where approximate noise measurements indicate quantum-limited pehrformance. A procedure is given for optimizing the bandwidth for this kind of amplifier, using a linearized circuit simulation while minimizing non-linearities.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
A windowed mean trajectory approximation for condensed phase dynamics
We propose a trajectory-based quasi-classical method for approximating dynamics in condensed phase systems. Building upon the previously developed optimized mean trajectory approximation that has been used to compute linear and nonlinear spectra, we borrow some ideas from filtering trajectory methods to obtain a novel semiclassical method for the dynamical propagation of density matrices. This new approximation is tested rigorously against standard multistate electronic models, spin-boson models, and models of the Fenna–Matthews–Olson complex. For dissipative systems, the current method is significantly better or as good as many other semiclassical methods available, especially at low temperatures and for off-diagonal density matrix elements, whereas for scattering models, the current method bears similar limitations as mean-field propagation schemes. All results are tested against the numerically exact hierarchical equations of motion method. In conclusion, the new method shows excellent agreement across various parameter regimes with numerically exact results, highlighting the robustness and accuracy of our approach.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Carbon dioxide stimulation of photosynthesis in Liquidambar styraciflua is not sustained during a 12-year field experiment
Elevated atmospheric CO 2 (eCO 2 ) often increases photosynthetic CO 2 assimilation (A) in field studies of temperate tree species, although there is evidence that the increases may decline through time due to biochemical and morphological acclimation, and environmental constraints. Indeed, at the free air CO 2 enrichment (FACE) study in Oak Ridge, Tennessee, A was increased in 12-year-old sweetgum trees following two years of ~40% enhancement of CO 2 . A was re-assessed a decade later to determine if initial enhancement of eCO 2 was sustained through time. Measurements were conducted at prevailing CO 2 and temperature on detached, re-hydrated branches using a portable gas exchange system. Photosynthetic CO 2 response curves (A versus the CO 2 concentration in the intercellular air space (C i ); or A-C i curves) were contrasted with earlier measurements using consistent leaf photosynthesis model equations. We accessed relationships between light-saturated photosynthesis (A sat ), maximum electron transport rate (J max ), maximum Rubisco activity (V cmax ) chlorophyll content and foliar nitrogen (N) and chlorophyll content. In 1999, light-saturated photosynthesis (A sat ) for eCO 2 treatments was 15.4 ± 0.8 μmol m -2 s -1 , 22% higher than aCO 2 treatments (P<0.01). By 2009, A sat declined to <50% of 1999 values, and there was no longer a significant effect of eCO 2 (A sat = 6.9 or 5.7 ± 0.7 μmol m -2 s -1 for eCO 2 or aCO 2 , respectively). In 1999, there was no treatment effect on area-based foliar N; however, by 2008, N content in eCO 2 foliage was 17% less than in aCO 2 foliage. Photosynthetic N use efficiency (A sat :N) was greater in eCO 2 in 1999 resulting in greater A sat despite similar N content, but the enhanced efficiency in eCO 2 trees was lost as foliar N declined to sub-optimal levels. There was no treatment difference in the declining linear relationships between J max or V cmax with declining N, or in the ratio of J max :V cmax through time. Results suggest that initial enhancement of photosynthesis to elevated CO 2 will not be sustained through time if nitrogen becomes limited.
54 ENVIRONMENTAL SCIENCES↗
Construction of mutually unbiased bases with cyclic symmetry for qubit systems
For the complete estimation of arbitrary unknown quantum states by measurements, the use of mutually unbiased bases has been well established in theory and experiment for the past 20 years. However, most constructions of these bases make heavy use of abstract algebra and the mathematical theory of finite rings and fields, and no simple and generally accessible construction is available. This is particularly true in the case of a system composed of several qubits, which is arguably the most important case in quantum information science and quantum computation. In this paper, we close this gap by providing a simple and straightforward method for the construction of mutually unbiased bases in the case of a qubit register. We show that our construction is also accessible to experiments, since only Hadamard and controlled-phase gates are needed, which are available in most practical realizations of a quantum computer. Moreover, our scheme possesses the optimal scaling possible, i.e., the number of gates scales only linearly in the number of qubits.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Maximum-confidence discrimination among symmetric qudit states
We study the maximum-confidence (MC) measurement strategy for discriminating among nonorthogonal symmetric qudit states. Restricting to linearly dependent and equally likely pure states, we find the optimal positive operator valued measure (POVM) that maximizes our confidence in identifying each state in the set and minimizes the probability of obtaining inconclusive results. The physical realization of this POVM is completely determined and it is shown that after an inconclusive outcome, the input states may be mapped into a new set of equiprobable symmetric states, restricted, however, to a subspace of the original qudit Hilbert space. By applying the MC measurement again onto this new set, we can still gain some information about the input states, although with less confidence than before. This leads us to introduce the concept of sequential maximum-confidence (SMC) measurements, where the optimized MC strategy is iterated in as many stages as allowed by the input set, until no further information can be extracted from an inconclusive result. Within each stage of this measurement our confidence in identifying the input states is the highest possible, although it decreases from one stage to the next. In addition, the more stages we accomplish within the maximum allowed, the higher will be the probability of correct identification. We will discuss an explicit example of the optimal SMC measurement applied in the discrimination among four symmetric qutrit states and propose an optical network to implement it.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Data Driven Optimization Framework for Volt-age Regulation in Distribution Systems
This letter proposes a data-driven optimization framework for voltage regulation problems to address the challenge of model inaccuracy and parameter varying. To achieve online voltage optimization, the recursive kernel regression and interior point methods are integrated. The IEEE 123-Bus system and EPRI Ckt5 feeder are selected to validate the effectiveness of the proposed data-driven optimization framework. The proposed method is also compared with a linear function based method.
Hong, Tianqi↗
MO-AB-BRA-04: Correct Identification of Low-Attenuation Intracranial Hemorrhage and Calcification Using Dual-Energy Computed Tomography in a Phantom System
Purpose: Intracranial hemorrhage and calcification with Single-Energy CT (SECT) attenuation below 100HU cannot be reliably identified using currently clinically available means. Calcification is typically benign but hemorrhage can carry a risk of intracranial bleeding and contraindicate use of anticoagulant therapies. A biologically-relevant phantom was used to investigate identification of unknown intracranial lesions using dual-energy CT (DECT) as a verification of prior lesion differentiation results. Methods: Prior phantom work investigating calcification and hemorrhage differentiation resulted in 3D-DECT raw data (water density, calcium density, 68keV) for a range of DECT protocol variations: image thicknesses (1.25, 2.5, 3.75, 5mm), CTDIvol (36.7 to 132.6mGy) and reconstruction algorithms (Soft, Standard, Detail). Acquisition-specific raw data were used to create a plane of optimal differentiation based on the geometric bisector of 3D-linear regression of the two lesion distributions. Verification hemorrhage and calcification lesions, ranging in size from 0.5 to 1.5cm, were created at varying attenuation from 50 to 100HU. Lesions were inserted into a biologically-relevant brain phantom and scanned using SECT (3.75mm images, Standard, 67mGy) and a range of DECT protocols (3.75mm images, Standard, [67, 105.6, 132.6mGy]). 3D-DECT data were collected and blinded for analysis. The 3D-DECT distribution of the lesion was then compared to the acquisition-matched geometric bisector plane and the mean lesion value’s position relative to the plane, indicating lesion identity, and the percentage of voxels on the identified side of the plane, indicating identification confidence, were derived. Results: 98% of the 120 lesions investigated were identified correctly as hemorrhage or calcification. 74% were identified with greater than 80% confidence. Increases in CTDIvol and lesion diameter were associated with increased identification confidence. Conclusion: Intracranial lesions of unknown etiology were identified with 80% confidence for 74% of lesions investigated. These phantom data suggest that the identification of intracranial lesions below 100HU is clinically feasible using DECT. This research was conducted at the MD Anderson Center for Advanced Biomedical Imaging in-part with equipment support from General Electric Healthcare.
60 APPLIED LIFE SCIENCES↗
WE-DE-201-08: Multi-Source Rotating Shield Brachytherapy Apparatus for Prostate Cancer
Purpose: To introduce a novel multi-source rotating shield brachytherapy (RSBT) apparatus for the precise simultaneous angular and linear positioning of all partially-shielded 153Gd radiation sources in interstitial needles for treating prostate cancer. The mechanism is designed to lower the detrimental dose to healthy tissues, the urethra in particular, relative to conventional high-dose-rate brachytherapy (HDR-BT) techniques. Methods: Following needle implantation, the delivery system is docked to the patient template. Each needle is coupled to a multi-source afterloader catheter by a connector passing through a shaft. The shafts are rotated by translating a moving template between two stationary templates. Shaft walls as well as moving template holes are threaded such that the resistive friction produced between the two parts exerts enough force on the shafts to bring about the rotation. Rotation of the shaft is then transmitted to the shielded source via several keys. Thus, shaft angular position is fully correlated with the position of the moving template. The catheter angles are simultaneously incremented throughout treatment as needed, and only a single 360° rotation of all catheters is needed for a full treatment. For each rotation angle, source depth in each needle is controlled by a multi-source afterloader, which is proposed as an array of belt-driven linear actuators, each of which drives a source wire. Results: Optimized treatment plans based on Monte Carlo dose calculations demonstrated RSBT with the proposed apparatus reduced urethral D{sub 1cc} below that of conventional HDR-BT by 35% for urethral dose gradient volume within 3 mm of the urethra surface. Treatment time to deliver 20 Gy with multi-source RSBT apparatus using nineteen 62.4 GBq {sup 153}Gd sources is 117 min. Conclusions: The proposed RSBT delivery apparatus in conjunction with multiple nitinol catheter-mounted platinum-shielded {sup 153}Gd sources enables a mechanically feasible urethra-sparing treatment technique for prostate cancer in a clinically reasonable timeframe.
60 APPLIED LIFE SCIENCES↗
Review—Development of Highly Active and Durable Hybrid Compressive Platinum Lattice Catalysts for Polymer Electrolyte Membrane Fuel Cells: Mathematical Modeling and Experimental Work
This review provides a comprehensive overview on the development of highly active and durable platinum catalysts with ultra-low Pt loadings for polymer electrolyte membrane fuel cells (PEMFCs) through a combined mathematical modeling and experimental work. First, simulation techniques were applied to evaluate the validity of the Tafel approximation for the calculation of the mass activity (MA) and specific activity (SA). A one-dimensional agglomeration model was developed and solved to understand the effects of exchange current density, porosity, agglomerate size, Nafion ® film thickness, and Pt loading on the MA and SA. High porosity (> 60%) and agglomerations at high Pt loadings cause the loss of the Tafel approximation and consequently the decrease in MA and SA. A new structure parameter was introduced to estimate the real porous structure using the fractal theory. The volumetric catalyst density was corrected by the fractal dimension (measured by Hg porosimetry), which gave a good agreement with the experimental values. The loading-dependent Tafel equation was then derived, which contains both the utilization and the non-linear scaling factor. Second, activated carbon composite support (ACCS) with optimized surface area, porosity, pore size, and pore size distribution was developed. The hydrophilic/hydrophobic ratio, structural properties (amorphous/crystalline ratio), and the number of active sites were optimized through metal-catalyzed pyrolysis. Stability of ACCS and Pt/ACCS were evaluated using an accelerated stress test (AST). The results indicated that Pt/ACCS showed no significant loss of MA and power density after 5,000 cycles at 1.0–1.5 V, while the commercial Pt/C catalysts showed drastic losses of MA and power density. Finally, monolayers of compressed Pt (core–shell-type Pt 3 Co 1 ) catalysts were structured by diffusing Co atoms (previously embedded in ACCS) into Pt. Compressive Pt lattice (Pt * ) catalysts were synthesized through an annealing procedure developed at the University of South Carolina (USC). The Pt * /ACCS catalyst showed high initial power density (rated) of 0.174 g Pt kW −1 and high stability (24 mV loss) at 0.8 A cm −2 after 30,000 cycles (0.6–1.0 V). The outstanding performance of Pt * /ACCS is due to the synergistic effect of ACCS and compressive Pt * lattice.
25 ENERGY STORAGE↗
HydraGNN v5.0
HydraGNN v5.0 expands the code base into a more portable, scalable, and flexible framework for scientific graph learning, with particular strength in atomistic machine-learning interatomic potentials and large-scale distributed training. The release adds Fully Sharded Data Parallel (FSDP) support alongside existing DDP and DeepSpeed paths, including FSDP-aware checkpointing and optimizer integration, and introduces a configurable multi-precision training workflow supporting FP32, BF16, and FP64 across GPUs and Intel XPUs. For atomistic modeling, HydraGNN v5.0 strengthens its MLIP capabilities through dynamic graph construction at every forward pass, energy-conserving force prediction via automatic differentiation, and per-atom energy loss formulations, while extending EGNN models to properly handle periodic boundary conditions. The release also broadens model expressiveness through graph-level attribute conditioning, adds new multi-task and model-parallel extensions such as MACE support and encoder/decoder branch optimization, and expands application coverage with integrated examples for datasets including OC25, Nabla2-DFT, QCML, Open Polymers 2026, and OPF. In parallel, HydraGNN v5.0 improves production readiness through performance optimizations for large-scale runs, stratified sampling and linear-regression preprocessing utilities, and tested installation scripts for DOE supercomputers including Frontier, Aurora, Perlmutter, and Andes. Overall, the release advances HydraGNN as a robust software platform for scalable graph neural networks across materials science, chemistry, and scientific machine learning workflows
Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
Holographic Imaging of Evolving Laser-Plasma Structures
In the 1870s, English photographer Eadweard Muybridge captured motion pictures within one cycle of a horse’s gallop, which settled a hotly debated question of his time by showing that the horse became temporarily airborne. In the 1940s, Manhattan project photographer Berlin Brixner captured a nuclear blast at a million frames per second, and resolved a dispute about the explosion’s shape and speed. In this project, we developed methods to capture detailed motion pictures of evolving, light-velocity objects created by a laser pulse propagating through matter. These objects include electron density waves used to accelerate charged particles, laser-induced refractive index changes used for micromachining, and ionization tracks used for atmospheric chemical analysis, guide star creation and ranging. Our “movies”, like Muybridge’s and Brixner’s, are obtained in one shot, since the laser-created objects of interest are insufficiently repeatable for accurate stroboscopic imaging. Our high-speed photographs have begun to resolve controversies about how laser-created objects form and evolve, questions that previously could be addressed only by intensive computer simulations based on estimated initial conditions. Resolving such questions helps develop better tabletop particle accelerators, atmospheric ranging devices and many other applications of laser-matter interactions. Our photographic methods all begin by splitting one or more “probe” pulses from the laser pulse that creates the light-speed object. A probe illuminates the object and obtains information about its structure without altering it. We developed three single-shot visualization methods that differ in how the probes interact with the object of interest or are recorded. (1) Frequency-Domain Holography (FDH). In FDH, there are 2 probes, like “object” and “reference” beams in conventional holography. Our “object” probe surrounds the light-speed object, like a fleas swarming around a sprinting animal. The object modifies the probe, imprinting information about its structure. Meanwhile, our “reference” probe co-propagates ahead of the object, free of its influence. After the interaction, object and reference combine to record a hologram. For technical reasons, our recording device is a spectrometer (a frequency-measuring device), hence the name “frequency-domain” holography. We read the hologram electronically to obtain a “snapshot” of the object’s average structure as it transits the medium. Our published work shows numerous snapshots of electron density waves (“laser wakes”) in ionized gas (“plasma”), analogous to a water wake behind a boat. Such waves are the basis of tabletop particle accelerators, in which charged particles surf on the light-speed wave, gaining energy. Comparing our snapshots to computer simulations deepens understanding of laser wakes. FDH takes snapshots of objects that are quasi-static --- i.e. like Muybridge’s horse standing still on a treadmill. If the object changes shape, FDH images blur, as when a subject moves while a camera shutter is open. Many laser-generated objects of interest do evolve as they propagate. To overcome this limit of FDH, we developed .... (2) Frequency-Domain Tomography (FDT). In FDT, 5 to 10 probe pulses are fired simultaneously across the object’s path at different angles, like a crossfire of bullets. The object imprints a “streaked” record of its evolution on each probe, which we record as in FDH, then recover a multi-frame “movie” of the object’s evolving structure using algorithms of computerized tomography. When propagation distance exceeds a few millimeters, reconstructed FDT images distort. This is because the lenses that image probes to detector have limited depth of field, like cameras that cannot focus simultaneously on both nearby and distant objects. But some laser-generated objects of interest propagate over meters. For these applications we developed … (3) Multi-Object-Plane Phase-Contrast Imaging (MOP-PCI). In MOP-PCI, we image FDT-like probes to the detector from multiple “object planes” --- like recording an event simultaneously with several cameras, some focused on nearby, others on distant, objects. To increase sensitivity, we exploit a phase-contrast imaging technique developed by Dutch Nobel laureate Fritz Zernike in the 1930s. Using MOP-PCI we recorded single-shot movies of laser pulse tracks through more than 10 cm of air. We plan to record images of meter-long tracks of electron bunches propagating through plasma in an experiment at the Stanford Linear Accelerator Center (SLAC). This will help SLAC scientists understand, optimize and scale small plasma-based particle accelerators that have applications in medicine, industry, materials science and high-energy physics.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
The Effects of Market Concentration on Residential Solar PV Prices: Competition, Installer Scale, and Soft Costs
Competition among residential solar photovoltaic (PV) installers may reduce PV price markups and yield lower prices. At the same time, competition may reduce installer experience and opportunities for cost reductions through learning-by-doing and economies of scale. These dynamics suggest that PV non-hardware or 'soft' costs and installed prices depend on the distribution of market shares among installers, also known as market concentration. This study leverages a rich data set of 226,769 residential PV systems to examine the relationship between market concentration, soft costs, and PV prices. The results show that PV prices are lower, on average, in more concentrated markets, i.e., markets with fewer installers or where few installers hold high market share. The study provides evidence that this relationship is non-linear, such that prices are minimized in markets with an optimal balance of the benefits of market concentration and the benefits of competition.
14 SOLAR ENERGY↗