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ARCHIMEDES is a process in which experiment optimization is performed utilizing sensitivities from MCNP and Whisper. A Gaussian process (GP) optimization is used to guide criticality experiment design. An example of this process is shown for LANL PF-4 plutonium casting.
The U.S. Department of Energy has a broad mission to ensure the nation’s security by addressing ongoing environmental challenges, developing novel energy production technologies, and mitigating nuclear security concerns. These efforts benefit from developing more effective semiconductor materials and devices. The research discussed in this report aims to further the development of these new electronics by improving implementations of vertical device structures, which offer theoretically better performance compared to lateral structures. Specifically, it reviews the background and development of a new and easy-to-use program for data processing and analysis from experiments run on vertical gallium nitride power devices. Current vertical structures fall short in critical performance metrics, such as On-Resistance and Breakdown Voltage, due to poor management of the device’s electric field. Junction termination extensions, or JTEs, are a field management technique that increases a device’s resilience to expected failure modes by controlling its surface electric fields. Each JTE design requires significant experimental validation, consisting of hundreds of tested devices, each outputting an enormous set of data points. The new software includes multiple methods of filtering large sets of device testing data to identify and remove flawed devices, automate device analyses, and provide statistical breakdowns for four metrics used to define the effectiveness of the JTE and the current carrying capacity of the device. These results can then be related back to fabrication techniques and device design, and in the future, be combined with processing simulations to further improve our understanding of the JTE mechanisms.
Abstract Thermal transition of organic solar cells (OSCs) constituent materials are often insufficiently researched, resulting in trial‐and‐error rather than rational approaches to annealing strategies to improve domain purity to enhance the power conversion efficiency. Despite the potential utility, little is known about the thermal transitions of the modern high‐performance acceptors Y6 and N3. Here, by using an optical method, it is discovered that the acceptor N3 has a clear solid‐state aggregation transition at 82 °C. This unusually low transition not only explains prior optimization protocols, but the transition informs and enables a double‐annealing method that can fine‐tune aggregation and the device morphology. Compared with 16.6% efficiency for PM6:N3:PC 71 BM control devices, higher efficiency of 17.6% is obtained through the improved protocol. Morphology characterization with x‐ray scattering methods reveals the formation of a multilength scale morphology. Moreover, the double‐annealing method is illustrated and easily transferred and validated with Y6‐based devices, using the transition of Y6 at 102 °C. As a result, the PCE improved from 16.0% to 16.8%. Design of high‐performance acceptors with yet lower aggregation transitions might be required for OSCs to successfully transition to low thermal budget industrial processing methods where annealing temperatures on plastic substrates have to be kept low.
Current research octane number (RON) and motor octane number (MON) gasoline performance characterization techniques use dated, complex engine testing methodology and limit researchers’ ability to easily characterize small volumes of experimental fuels. A novel methodology is presented that correlates measured ignition delay (ID) time to RON in an Advanced Fuel Ignition Delay Analyzer (AFIDA) constant-volume combustion chamber device at a single pressure/temperature condition, with an r2 of 0.99 and standard error (SE) of 1.0. The correlation of the slope of the ID time between two additional temperature points to octane sensitivity (S) produces an r2 of 0.97 and SE of 0.69; however, fuels with S>12 are indistinguishable. These results are based on methodology calibration using 31 primary and toluene reference fuels containing 0%-40% ethanol with RON values ranging from 85 to 113. Validation of these methods using a 102-sample fuel matrix spanning an array of base fuels and additive chemistry designed to test the robust applicability of the method, along with pump gasoline and high-octane surrogate blend samples, demonstrates an r2 of 0.94 and SE of 1.3 for the RON correlation over all samples, whereas the equivalent S correlation produces an r2 of 0.78 and SE of 1.2 by excluding two additives, 3-pentanone and diisobutylene, which displayed poor S correlation results. This novel AFIDA analysis method can be performed in 1 h and with 40 mL of fuel, offering significant improvements in time and volume requirements over traditional techniques.
The performance of the electromagnetic calorimeter of the ALICE experiment during operation in 2010–2018 at the Large Hadron Collider is presented. After a short introduction into the design, readout, and trigger capabilities of the detector, the procedures for data taking, reconstruction, and validation are explained. The methods used for the calibration and various derived corrections are presented in detail. Subsequently, the capabilities of the calorimeter to reconstruct and measure photons, light mesons, electrons and jets are discussed. The performance of the calorimeter is illustrated mainly with data obtained with test beams at the Proton Synchrotron and Super Proton Synchrotron or in proton-proton collisions at $\sqrt{s}$ = 13 TeV, and compared to simulations.
elm-diagnostics is a Python package for computing diagnostic analyses and visualizations for the E3SM Land Model (ELM) component and is meant to support new feature development in ELM. The tool reads model history files and performs quantitative analyses including budget-closure checking, variable transformations, temporal aggregations, and statistical summaries to support model evaluation, validation, and scientific interpretation. The framework is designed for extensibility, with modular architecture enabling straightforward addition of new diagnostic methods, derived variables, analysis types, visualization approaches, and model-specific adaptations
The scope of this work addresses key issues associated with losses associated with the detonation wave and other processes internal to the RDE operation, as well as it develops modeling tools for the evaluation of these losses and exhaust emissions in RDEs. The main challenge in studying RDEs is that RDE performance is highly reliant on the specifics of the design so much so that simple/canonical systems alone cannot provide useful engineering information, but practical RDE designs are sufficiently complex and involve extreme operational environments that detailed access either experimentally (laser diagnostics, for instance) or computationally (direct numerical simulations) are as yet to become practical. To overcome this challenge, we have conducted a combined experimental/simulation/analytical study investigating key phenomena that control the characteristics of operation of RDEs. As a result, the study has developed tools and methods that can be used to evaluate performance and design approaches using reduced-physics models, with the assumptions validated using detailed simulations, and the model prediction tested using experimental observations. The specific objectives of the research were: (1) Develop and demonstrate a low-loss fully axial injection concept, taking advantage of stratification effects to alter the detonation structure and position the wave favorably within the combustor; (2) Obtain stability and operability characteristics of an RDE across operating conditions to aid in the development of operability and performance rules for the operations of other systems; and (3) Develop quantitative metrics for performance gain as well as quantitative description of the loss mechanisms through a combination of diagnostics development, reduced-order modeling, and detailed simulations. The work conducted here has made contribution on design of low-loss inlets that has broad application within the power generation industry for use with pressure gain combustion. The operability and stability of different designs, while focusing on axial air inlet designs, has been analyzed. The effect of nozzle and injection conditions was studied. Models and simulations of exhaust emissions, focusing on NOx emission has been developed and used to investigate how operation of the RDE affect NOx production using Lagrangian analysis of RDE simulations. This work has built on previous programs, with the goal of further understanding operation of RDEs and elevate the readiness of design consideration. In addition, a suite of diagnostic and modeling tools have been developed to obtain quantitative metrics on performance based on measurements, which can be readily transferred to other experimental configurations.
Precise characterization of experimental radiation flow is required to validate the high energy density physics models, numerical methods, and codes that are used to simulate radiation-hydrodynamics phenomena such as thermal radiation transport in stochastic media. The Cassio code is used to simulate thermal radiation flow through inhomogeneous, stochastic-media-foam configurations containing optically thick clumps dispersed within an optically thin background aerogel. Cassio can model small inhomogeneous problems directly, but most problems require approximations to meet computer limitations on run-times and memory usage. Various examples of these approximations are methods that produce, in one calculation, an ensemble-averaged solution and associated standard deviation; reduced spatial dimensionality with approximate geometries; and full material homogenization with no geometric detail. Cassio simulations are used to design experiments at the OMEGA-60 Laser Facility that can measure the radiation flow using the spatially resolved COAX absorption spectroscopy diagnostic. The experimental platforms flow radiation through foam targets ranging from a background-only aerogel, to a single configuration of a specified stochastic medium, to a fully homogenized foam of the background and clump materials. Under constant total clump mass, larger clumps (here, larger than 10 μm diameter) will mix more slowly with the background such that the bulk radiation flow is faster than it would be in a fully homogenized material. The COAX platform can be used to infer temperature and density profiles in both the background material and clumps, simultaneously, and therefore to differentiate radiation flow in a range of stochastic and homogeneous media.
The rapid growth and plummeting cost of solar energy have spurred growing interest in using CO 2 electrolysis to produce chemicals and fuels as an alternative to conventional petrochemical processes. High-temperature (>800 °C) solid oxide electrolyzers that convert CO 2 into CO and O 2 have recently become commercially available. Low-temperature electrolysis cells offer the prospect of more convenient and flexible operation, which is critical for utilizing intermittent solar energy, and provide access to more valuable C 2+ products such as ethylene, ethanol, and propanol. Over the past 10 years, research in this area has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices. Leveraging insights from fuel cells and membrane water electrolyzers, researchers have developed electrolysis cells with gas diffusion electrodes (GDE) that have demonstrated high CO 2 electrolysis current densities (>100 mA cm –2 ) as well as promising selectivity and stability. Despite these advances, the energy efficiency (electrical energy-to-product) and carbon efficiency (CO 2 -to-product) of low-temperature CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal source of efficiency losses is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH – ) to form carbonate (CO 3 2– ). Carbonate formation imposes steady-state electrolysis conditions that result in large voltage and CO 2 losses for all known (photo)electrochemical CO 2 cells. While much current research remains focused on CO 2 reduction catalyst design, this largely overlooked CO 3 2– problem presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels. The project pursues an integrated, multi-PI research effort that establishes a fundamental science of CO 3 2– management. PI Kanan and Co-PI Mani’s contribution to the project is to evaluate strategies to mitigate the CO 3 2– problem by changing the properties of the electrolyte and the environment in which CO 2 reduction catalysis takes place. Experimental studies showed that electrolytes composed of a high concentration of both CO 3 2– and HCO 3 – , which serve as moderately alkaline buffers, improved the cell voltage by compared to all-HCO 3 – electrolytes, but these buffered systems still show substantial CO 2 uptake that reduces pH over time. Computational studies developed a homogenized model of a CO 2 reduction catalyst layer that permits a low-cost exploration of the high-dimensional parameter space associated with catalyst layers on gas diffusion electrodes. The model was validated by accurately reproducing experimental data for the related but simpler reaction of CO reduction and then used to probe the effects of catalyst layer architecture on CO 2 reduction. Minimizing the size of catalyst and hydrophobic domains in the catalyst layer is predicted to mitigate CO 3 2– formation and thereby enable prolonged operation at elevated pH. In support of the CO 2 electrolysis studies, a new method for rapidly prototyping electrochemical cells was developed and validated. The method uses a combination of 3D printing and electroless plating to generate conductive cell components for evaluating new cell designs. The carbonate problem encompasses mass transport processes and acid-base reactions that are relevant to many other electrochemical systems. Investigation of strategies to address the carbonate problem led to an additional line of inquiry into the physicochemical phenomena that determine the efficiency of electrochemical acid-base production, which has numerous applications in the broader field of carbon management. New strategies for using the supporting electrolyte to inhibit H + /OH – recombination in electrochemical acid-base production were evaluated, leading to the development of a novel acid-base producing system that eliminates the need for ion exchange membranes and exhibits promising efficiency and current densities for scalable applications.
Dynamic Energy Transport and Integration Lab (DETAIL) at Idaho National Laboratory is to support experimental demonstration and validation research on Nuclear-Renewable Hybrid Energy System [1]. The Thermal Energy Distribution System (TEDS) is a thermal-hydraulic flow loop in DETAIL with its own dedicated control system to support the integration of co-located multiple experimental systems, where a packed-bed thermal energy storage (TES) is installed as a thermal buffer and storage unit. Among various TES options, the packed-bed TES is adopted in TEDS because it offers a low-cost single-tank thermal storage option compared to the traditional two-tank TES. However, since the TES tank is filled with granular fillers having different thermophysical properties from those of TES tank wall, there is a potential thermo-mechanical issue to be carefully addressed like thermal ratcheting which may pose a significant design concern for the packed-bed TES tank. Thermal ratcheting is a thermomechanical process caused by the repeated rearrangement of granular filler inside a TES tank during continuous thermal cycling operation of the packed-bed TES system. If the thermally induced stress exceeds the yield strength of a TES tank wall, catastrophic consequences may happen like rupture of the TES tank. Thus, it is important to understand the phenomenon to ensure the robust operation of the packed-bed TES tank. Given that thermal ratcheting is caused by complex interaction of thermal transport in the porous bed and solid mechanics, the accurate prediction of transient thermal behavior of the packed-bed TES tank, which is the focus of this paper, is critical to the reliable thermal ratcheting analysis. This paper discusses the numerical modeling, simulation, and validation studies that are ongoing at INL to investigate the transient thermal behavior of the packed-bed TES. Of particular concern is the transient thermal process occurring in the packed-bed TES unit that is operated in conjunction with the INL TEDS. The main goal of this research is three-fold: (i) provide preliminary insights into the transient thermal behavior of the TEDS TES tank, (ii) support the thermal measurement and validation plan for TEDS experiment, and (iii) provide transient thermal boundary conditions to support the reliable thermal ratcheting analysis of the TEDS TES tank. For the transient thermal modeling and analysis, a CFD model was developed, and the validity of the modeling approach was examined via comparing the numerical simulation results with the experimental data obtained from various design characteristics of packed-bed TES tanks. Then, the present modeling method was applied for the transient thermal analysis of the TEDS TES tank, and the results are discussed along with the potential improvement of data acquisition strategy for the future TEDS experiments for more precise validation study.
This chapter presents the activity conducted by the ITPA topical group (TG) on Diagnostics over about the last 15 years. Following a general introduction of the ITER Diagnostics led by their measurement roles, the document is organized in several subchapters detailing the design support, research and development activity conducted by each of the specialist working groups (WGs) of the TG. Please note that the magnetic diagnostics were supported at the TG without a specific WG. Their status is included in the general introduction. In the following some highlights of the subchapter’s contents are provided. Recent advances in ITER first wall (FW) diagnostics for the measurements of plasma-metallic wall interaction in support of the ITER research plan are reported. An InfraRed imaging Video Bolometer for ITER has been developed and tested on several tokamaks to measure the radiated power loss. A laser-induced breakdown spectroscopy (LIBS) technique which utilizes a pulsed laser beam to ablate locally by forming a crater, will measure local tritium inventory in the FW material. Real-time Residual Gas Analyzers will measure the neutral gas composition in a divertor port and an equatorial port during plasma operation. Due to the full metallic FW environment, the plasma-wall interaction in ITER will face several challenges such as the compromised radiated power and divertor heat flux measurements by reflection. Ray tracing and analysis codes have been developed to eliminate and correct the effects of reflection in the measurements. The characteristics of the reflecting surfaces depending on the roughness and angle of the incidence have been measured by dedicated experiments, and the results were applied to the reflection elimination. For the measurement of the metallic impurity radiation induced by eroded metallic atoms, a vacuum ultraviolet spectrometer has been developed and tested. An extensive thermonuclear diagnostic suite will be required to support the operation of ITER and the planned experimental program for future burning plasma experiments. Due to the harsh environmental conditions, the implementation of diagnostic systems in ITER is a major challenge. These conditions include high levels of neutron and gamma fluxes, neutron heating, particle bombardment. Therefore, the selection and design of diagnostic systems must take into account a number of phenomena previously unseen in diagnostic design. For this reason, the measurement of neutrons and confined or lost fast ions, with particular emphasis on alpha particles, is critical to ITER. The diagnostics associated with these measurements will be important for future plasma-burning experiments at ITER. The high neutron emission and very large plasma size in ITER make neutron diagnostics the main diagnostic method used to measure plasma parameters such as fusion power, fusion power density, ion temperature, energy of fast ions and their spatial distributions in the plasma core. Active spectroscopy techniques are methods where a neutral particle beam is injected into the plasma and information on plasma parameters is extracted from the measurement of line emission resulting from the beam-plasma interaction, either by plasma ions or by beam atoms. Spatial localization is achieved by crossing the beamline and multiple observation lines. The ITER plasma will be a high temperature, moderately dense, fully ionized collisional plasma. The plasma facing surfaces are principally metallic being fashioned from beryllium or tungsten but many other elements, arising from either structural or from operational needs, may enter this plasma. The energy range of the emitted photons range from meV (infra-red) to multi keV (x-rays) and originate from all areas of the plasma volume. The primary role of passive emission diagnostics is to identify what is in the plasma from spectral signatures. Extracting quantitative information from these measurements such as impurity content, ion temperature, rotation, degree of detachment and radiated power depends on calibrated instruments, a physics model of the atomic and molecular processes and plasma transport and an analysis workflow that takes into account environmental effects such as reflections. The particular needs for ITER have prompted a multi-machine, many-year effort to address all these aspects and this chapter reviews the work on diagnostic design, experiments and new analysis techniques. An overview of the laser diagnostics to be implemented on ITER is also provided in this paper. This includes descriptions of the Thomson scattering in the core, edge and divertor regions, polarimetry and interferometry diagnostics used for measuring plasma density and also measurements of helium density in the divertor using Laser Induced Flourescence. Techniques which can allow improvements on current measurements are also addressed in particular expanding poloidal polarimetry measurements to measure field fluctuations and proposed use of dispersion interferometery which has a number of advantages over existing methods. This paper identifies particular areas where further research and testing on existing tokamaks is useful even at this advanced stage to inform the design of diagnostics for ITER. Outstanding areas of concern for the implementation of laser diagnostics, in particular with a view to reliable operation are identified. An overview of the latest developments of microwave diagnostic systems and techniques is given. The primary focus is the contributions for ITER—the next step burning plasma experiment—which is supplemented by describing recent progress of techniques applicable for fusion experiments beyond ITER. The contributions are intentionally kept concise, and are being supplemented by a rich list of references for further studies. Radiation induced effects are receiving continuous and well-deserved attention of the ITER diagnostic community and they are in many cases one of the primary design drivers of the ITER diagnostic systems. The paper summarizes recent progress in this area focusing primarily on the ITER diagnostics but in some cases provides also outlook for the possible solutions for even more demanding radiation environment of fusion reactors beyond ITER. Despite advancements in the area of modeling and simulation of various radiation induced effects, experimental testing in a nuclear environment as close as possible to the target one is still seen as unavoidable for proper qualification of particular diagnostic functional elements. Recent advancement within three diagnostic areas: optical diagnostics, magnetics and bolometers is covered. Encouraging results on qualification of silica glass vacuum window assemblies are presented. In the area of magnetic sensors, progress of irradiation tests performed on ITER in-vessel LTCC inductive sensors is presented with outlook for novel technological approaches to inductive sensors utilizing thick printing and photolithography technologies being highlighted. Summary of advancements in the area of steady state magnetic field sensors based on Hall effect is given. New results of neutron irradiation test of the ITER borosilicate glass inserts for vacuum electrical feedthroughs are summarized finding negligible swelling at target level of neutron fluence. Off-line irradiation tests of fiber optic current sensors for plasma current measurement demonstrated that both for gamma doses up to 5 MGy and a total neutron fluence up to 10 15 cm −2 , radiation induced changes are still compatible with required measurement accuracy on ITER. The ITER bolometers are given as an example how considering radiation effects may influence the diagnostic design. Finally, outlook for future main R&D directions is outlined. All optical and laser-based diagnostics in ITER will be using mirrors to guide plasma radiation toward detectors, cameras and sensors. In the hostile plasma, radiation and particle environment the optical characteristics of diagnostic mirrors will degrade directly affecting the entire performance of involved diagnostic systems. An assessment of factors affecting mirror performance is provided. Among the prime adverse factors are deposition of plasma impurities, sputtering of mirror surface and steam ingress in the vicinity of mirrors. Within the International Tokamak Physics Activity with active support by ITER central team and domestic agencies, the structured research and development (R&D) program on mitigation of risks for diagnostic mirrors is underway. Within this program the mirror material development, the passive mitigation of mirror degradation by using diagnostic ducts and shutters along with an active mirror recovery program comprising the in-situ mirror cleaning and calibration is underway. Recent developments in diagnostic mirror R&D are described in this Chapter along with an example of their implementation of R&D solutions in ITER Infrared Thermography diagnostic. An assessment of still open engineering and physics questions, considerations on mirror risks during an early phase of ITER operation are given along with an overview of diagnostic mirror evolution in the late ITER operation stage toward the demonstration fusion power plant. Several crucial areas of diagnostic R&D outlined in ITER Research Plan are addressed. The basic control groups in a fusion reactor can be broken-down in five categories: (1) plasma position, magnetic configuration, and plasma current control, (2) profile control and confinement optimization, (3) MHD control and suppression, (4) edge dissipation control, radiation and plasma exhaust control and (5) break-down optimization. These categories are coupled via the physics (a control action in one domain will affect the other domains) and via shared actuators (e.g. ECRH for impurity accumulation avoidance, current density distribution control and MHD suppression). Consequently, a supervisory control system should determine the priority of the various control tasks, their couplings, and the interfaces with the safety and interlock system. For the systematic development of the various controllers taking the complexity of the plasma and the control system into account, a model-based approach is required. A short historical overview is given of the developments in systems and control theory and control engineering with special emphasis on those developments that are most relevant for Nuclear Fusion research and operation. An overview is given of the state of the field of fusion plasma control for the control categories. It will be shown how synthetic diagnostics are being developed in ITER and how they are used in diagnostic design and design validation and how they can be in model-based controller synthesis using relatively simple models. In modern control methods, multiple diagnostics are used to constrain relatively simple models. The constrained models provide an estimate for the state. This opens the route to state controllers, such as model predictive control. A major challenge in nuclear fusion research is the coherent combination of data from heterogeneous diagnostics and modeling codes for machine control and safety as well as physics studies. Measured data from different diagnostics often provide information about the same subset of physical parameters. Additionally, information provided by some diagnostics might be needed for the analysis of other diagnostics. A joint analysis of complementary and redundant data allows, e.g. to improve the reliability of parameter estimation, to increase the spatial and temporal resolution of profiles, to obtain synergistic effects, to consider diagnostics interdependencies and to find and resolve data inconsistencies. Physics-based modeling and parameter relationships provide additional information improving the treatment of ill-posed inversion problems. A coherent combination of all kind of available information within a probabilistic framework allows for improved data analysis results. The concept of integrated data analysis (IDA) in the framework of Bayesian probability theory is outlined and contrasted with conventional data analysis. Components of the probabilistic approach are summarized and specific ingredients beneficial for data analysis at fusion devices are discussed.
Abstract Surrogate-based Bayesian optimization has been widely applied in design optimization to increase sampling efficiency. However, the cost for each evaluation of the objective function can still be very high when physical experiments or large-scale simulations are involved. Multi-fidelity Bayesian optimization is the new approach to further improve the sampling efficiency by reducing the number of expensive samples at the highest fidelity level and supplementing them with less expensive ones at low-fidelity levels. In this paper, a new consequential improvement (CI) acquisition function is proposed to allow for the simultaneous selection of the solution and the fidelity level in problems with a known hierarchy of fidelity levels. The new CI acquisition function incorporates the consequential effectiveness of objective improvement with the considerations of cost, accuracy, and validity differences between high- and low-fidelity samples in engineering practice. The new method of multi-fidelity Bayesian optimization based on the CI is demonstrated with several analytical and simulation-based design examples. In the simulation-based design optimization example, the results show that the CI acquisition function has a decisive advantage in the sampling efficiency over the other methods of multi-fidelity Bayesian optimization with simultaneous selection. The results indicate that the proposed method is particularly advantageous in solving high-dimensional problems and when large cost ratios between high- and low-fidelity evaluations exist and high-fidelity validation is mandatory. Furthermore, the method robustly avoids the prevalent issue of over sampling at low-fidelity levels.
Urban ecological studies have the potential to extend our understanding of socio-ecological systems beyond that of an individual city or region. Cross-comparative empirical work and synthesis are imperative to develop a general urban ecological theory. This can be achieved only if studies are replicable and generalizable. Transparency in methods reporting facilitates generalizability and replicability by documenting the decisions scientists make during the various steps of research design; this is particularly true for sampling design and selection because of their impact on both internal and external validity and the potential to unintentionally introduce bias. Three interdependent aspects of sample design are study sample selection (e.g., specific organisms, soils, or water), sample specification (measurement of specific variable of interest), and site selection (locations sampled). Of these, documentation of site selection—the where component of sample design—is underrepresented in the urban ecology literature. Using a stratified random sample of 158 papers from 12 major urban ecology journals, we investigated how researchers selected study sites in urban ecosystems and evaluated whether their site selection methods were transparent. We extracted data from these papers using a 50-question, theory-based questionnaire and a multiple-reviewer approach. Our sample represented almost 45 years of urban ecology research across 40 different countries. We found that more than 80% of the papers read were not transparent in their site selection methodology. We do not believe site selection methods are replicable for 70% of the papers read. Key weaknesses include incomplete descriptions of populations and sampling frames, urban gradients, sample selection methods, and property access. Low transparency in reporting the where methodology limits urban ecologists’ ability to assess the internal and external validity of studies’ findings and to replicate published studies; it also limits the generalizability of existing studies. The challenges of low transparency are particularly relevant in urban ecology, a field where standard protocols for site selection and delineation are still being developed. These limitations interfere with the fields’ ability to build theory and inform policy. We conclude by offering a set of recommendations to increase transparency, replicability, and generalizability.
Microchannel recuperators can achieve high-efficiency power cycles and chemical reactions by recovering waste heat from hot turbine exhaust and chemical reaction streams. However, the industrial application of microchannel recuperators are restricted by the high cost of patterning and bonding. The objective of this study was thus to investigate new methods for producing microchannel recuperators for emerging markets. Based on greenfield cost estimates, process designs based on stamping, laser welding and vacuum brazing of 316L stainless steel laminae were found to be more economical than conventional photochemical machining and diffusion bonding. Subsequently, validation experiments were conducted to produce stamped microchannel components using cost model parameters. At a mass flow rate of 0.99 g/s, the test article made with laser welding was found to provide higher effectiveness than the test article produced using vacuum brazing. Preliminary investigations showed that residual stresses during laser welding of the laminae led to significant warpage, collapsing channels and making lamina-to-lamina fit up challenging. In contrast, the test article produced by vacuum brazing of stamped laminae showed no clogging and 4.6% and 10.5% channel height standard deviation for the cold and hot channels, respectively. Channel variation in the vacuum brazing sample was determined to be caused by misregistration of laminae during brazing. In future work, efforts are needed to choose cheaper, more ductile brazing foils as well as design a brazing fixture to improve lamina-to-lamina registration.
Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.
An islanded microgrid can be used to serve critcal load as a resiliency source when a severe outage occurs. In an islanded mode, control of a microgrid relies on the communication system significantly. Hence, microgrids are cyberphysical systems and, therefore, the cyber system plays a crucial role in the performance of the cyber-power system. A microgrid control scheme is proposed for power dispatch and regulation based on the droop and proportional-integral (PI) feedback control. The proposed control strategy is validated for transient stability following dynamic events. To evaluate the impact of a networked control system on control performance, a cyber model is developed to represent data acquisition periods and communication delays. An analytical method is proposed to determine the critical values for the data reporting periods and communication delays. The analytical method based on a state space model of a networked control system is applicable for large-scale systems. A 2-dimensional stability region of a microgrid in the space of cyber parameters can be obtained by the proposed method, and the critical values of cyber parameters are determined based on the stability region. Simulation results validate that the design of a microgrid as a cyber-physical system needs to be guided by critical values for the data reporting period and communication delay to prevent system instability.
Variational quantum algorithms (VQAs) offer a promising near-term approach to finding optimal quantum strategies for playing non-local games. These games test quantum correlations beyond classical limits and enable entanglement verification. In this work, we present a variational framework for the Magic Square Game (MSG), a two-player non-local game with perfect quantum advantage. We construct a value Hamiltonian that encodes the game’s parity and consistency constraints, then optimize parameterize quantum circuits to minimize this cost. Our approach build on the stabilizer formalism, leverages commutation structure for circuit design, and is hardware-efficient. Compared to existing work, our contribution emphasizes algebraic structure an interpretability. We validate our method through numerical experiments and outline generalizations to larger games.
After the recent results on Bi-2212 superconductive magnets realized and tested in canted cosine-theta and solenoid designs, respectively, at Lawrence Berkeley National Laboratory (LBNL) and NHMFL, the first Bi-2212 stress-managed cosine-theta insert magnet is in the assembly phase at Fermilab. This insert will be part of the first hybrid cosine-theta magnet made of Nb3Sn outer layers within the US-MDP effort to reach 20 T bore field. This paper reports the analytical analysis of the cosine-theta Nb3Sn/Bi-2212 hybrid magnet. As an introduction, it shows the validation of the finalized HTS coils' design optimized using the ROXIE code. Subsequently, it reports the parameters, logic, and implementation method of the 2D electromagnetic and mechanical FEM analysis of the LTS/HTS hybrid magnet. Results from the ANSYS detailed model made with sub-modeling geometry are compared with the homogeneous model implemented in the past. Moreover, a Python code was implemented to simulate the current degradation due to stresses in the detail-modeled conductor areas. The current degradation is introduced in the simulation dynamics for both conductors as an iteration process during the energization load step only after applying pre-stress and thermal loads. The numerical and graphic results of the 2D cosine-theta LTS/HTS magnet cross-section will be described and analyzed.