Demand response for variable renewable energy integration: A proposed approach and its impacts
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Much of the structure of cosmological correlators is controlled by their singularities, which in turn are fixed in terms of flat-space scattering amplitudes. An important challenge is to interpolate between the singular limits to determine the full correlators at arbitrary kinematics. This is particularly relevant because the singularities of correlators are not directly observable, but can only be accessed by analytic continuation. In this paper, we study rational correlators — including those of gauge fields, gravitons, and the inflaton — whose only singularities at tree level are poles and whose behavior away from these poles is strongly constrained by unitarity and locality. We describe how unitarity translates into a set of cutting rules that consistent correlators must satisfy, and explain how this can be used to bootstrap correlators given information about their singularities. We also derive recursion relations that allow the iterative construction of more complicated correlators from simpler building blocks. In flat space, all energy singularities are simple poles, so that the combination of unitarity constraints and recursion relations provides an efficient way to bootstrap the full correlators. In many cases, these flat-space correlators can then be transformed into their more complex de Sitter counterparts. As an example of this procedure, we derive the correlator associated to graviton Compton scattering in de Sitter space, though the methods are much more widely applicable.
Aerosol pH governs many important atmospheric processes that occur in the marine boundary layer, including regulating halogen and sulfur chemistries, and nutrient fertilization of surface ocean waters. In this study, we investigated the acidity of PM1 over the eastern North Atlantic during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) aircraft campaign. The ISORROPIA-II thermodynamic model was used to predict PM1 pH and water. We first investigated the sensitivities of PM1 pH and water predictions to gas-phase NH3 and HNO3 concentrations. Our sensitivity analysis indicated that even though NH3 and HNO3 were present at very low concentrations in the eastern North Atlantic during the campaign, PM1 pH calculations can still be sensitive to NH3 concentrations. Specifically, NH3 was needed to constrain the pH of populations of PM1 that had low mass concentrations of NH4+ and non-volatile cations (NVCs). We next assumed that gas-phase NH3 and HNO3 concentrations during the campaign were 0.15 and 0.09 µg m−3, respectively, based on previous measurements conducted in the eastern North Atlantic. Using the assumption that PM1 were internally mixed (i.e., bulk PM1), we determined that PM1 pH ranged from 0.3–8.6, with a mean pH of 5.0 ± 2.3. The pH depended on both Hair+ and Wi. Hair+ was controlled primarily by the NVCs/SO42− molar ratio, while Wi was controlled by the SO42− mass concentration and RH. Changes in pH with altitude were driven primarily by changes in SO42−. Since aerosols in marine atmospheres are rarely internally mixed, the scenario where non-sea salt species and sea-salt species were present in two separate aerosol modes in the PM1 (i.e., completely externally mixed) was also considered. Smaller pH values were predicted for the aerosol mode comprised only of non-sea salt species compared to the bulk PM1 (difference of around 1 unit on average). This was due to the exclusion of sea-salt species (especially hygroscopic alkaline NVCs) in this aerosol mode, which led to increases in Hair+ values and decreases in Wi values. This result demonstrated that assumptions of aerosol mixing states can impact aerosol pH predictions substantially, which will have important implications for evaluating the nature and magnitude of pH-dependent atmospheric processes that occur in the marine boundary layer.
Interstitial collagenase plays an important role in both the normal and pathological remodeling of collagenous extracellular matrices, including skeletal tissues. The enzyme is a member of the family of matrix metalloproteinases. Only one rodent interstitial collagenase has been found but there are two human enzymes, human collagenase-1 and -3, the latter being the homologue of the rat enzyme. In developing rat and mouse bone, collagenase is expressed by hypertrophic chondrocytes, osteoblasts, and osteocytes, a situation that is replicated in a fracture callus. Cultured osteoblasts derived from neonatal rat calvariae show greater amounts of collagenase transcripts late in differentiation. These levels can be regulated by parathyroid hormone (PTH), retinoic acid, and insulin-like growth factors, as well as the degree of matrix mineralization. Much of the work on collagenase in bone has been derived from studies on the rat osteosarcoma cell line, UMR 106-01. All bone-resorbing agents stimulate these cells to produce collagenase mRNA and protein, with PTH being the most potent stimulator. Determination of secreted levels of collagenase has been difficult because UMR cells, normal rat osteoblasts, and rat fibroblasts possess a scavenger receptor that removes the enzyme from the extracellular space, internalizes and degrades it, thus imposing another level of control. PTH can also regulate the abundance of the receptor as well as the expression and synthesis of the enzyme. Regulation of the collagenase gene by PTH appears to involve the cAMP pathway as well as a primary response gene, possibly Fos, which then contributes to induction of the collagenase gene. The rat collagenase gene contains an activator protein-1 sequence that is necessary for basal expression, but other promoter regions may also participate in PTH regulation. Thus, there are many levels of regulation of collagenase in bone perhaps constraining what would otherwise be a rampant enzyme.
Approximately 240 Tg of mineral dust aerosol are transported annually from Saharan Africa to the Atlantic Ocean. Dust affects the Earth radiation budget, and plays direct (through scattering and absorption of radiation) and indirect (through modification of cloud properties and environment) roles in climate. Deposition of dust to the surface provides an important nutrient source to terrestrial and oceanic ecosystems. Dust is additionally a contributor to adverse air quality. Among the tools toward understanding the lifecycle and impacts of mineral dust aerosols are numerical models. Important constraints on these models come from quantitative satellite observations, like those from the space-based Moderate Resolution Imaging Spectroradiometer (MODIS). In particular, Kauhan et al. [2005] used MODIS aerosol observations to infer transport and deposition fluxes of Saharan dust over the Atlantic, Caribbean, and Amazonian basins. Those observations are used here to constrain the transport of dust and its interannual variability simulated in the NASA GEOS-5 general circulation model and data assimilation system. Significant uncertainty exists in the MODIS-derived fluxes, however, due to uncertainty in the wind fields provided by meteorological analyses in this region. That same uncertainty in the wind fields is manifest in our GEOS-5 simulations of dust distributions. Here we use MODIS observations to investigate the seasonality and location of the Saharan dust plume and explore through sensitivity analysis of our model the meteorological controls on the dust distribution, including dust direct radiative effects and sub-gridscale source and sink processes.
An approximation method and system are provided for more quickly controlling a prosthetic or other device by reducing computational processing time in a muscle model that can be used to control the prosthetic. For a given muscle, the approximation method can quickly compute polynomial structures for a muscle length and for each associated moment arms, which may be used to generate a torque for a joint position of a physics model. The physics model, in turn, produces a next joint position and velocity data for driving a prosthetic. The approximation method expands the polynomial structures as long as expansion is possible and sufficiently beneficial. The computations can be performed quickly by expanding the polynomial structures in a way that constrains the muscle length polynomial to the moment arm polynomial structures, and vice versa.
Missions to small bodies, such as comets or asteroids, require autonomous guidance for descent to these small bodies. Such guidance is made challenging by uncertainty in the position and velocity of the spacecraft, as well as the uncertainty in the gravitational field around the small body. In addition, the requirement to avoid collision with the asteroid represents a non-convex constraint that means finding the optimal guidance trajectory, in general, is intractable. In this innovation, a new approach is proposed for chance-constrained optimal guidance with non-convex constraints. Chance-constrained guidance takes into account uncertainty so that the probability of collision is below a specified threshold. In this approach, a new bounding method has been developed to obtain a set of decomposed chance constraints that is a sufficient condition of the original chance constraint. The decomposition of the chance constraint enables its efficient evaluation, as well as the application of the branch and bound method. Branch and bound enables non-convex problems to be solved efficiently to global optimality. Considering the problem of finite-horizon robust optimal control of dynamic systems under Gaussian-distributed stochastic uncertainty, with state and control constraints, a discrete-time, continuous-state linear dynamics model is assumed. Gaussian-distributed stochastic uncertainty is a more natural model for exogenous disturbances such as wind gusts and turbulence than the previously studied set-bounded models. However, with stochastic uncertainty, it is often impossible to guarantee that state constraints are satisfied, because there is typically a non-zero probability of having a disturbance that is large enough to push the state out of the feasible region. An effective framework to address robustness with stochastic uncertainty is optimization with chance constraints. These require that the probability of violating the state constraints (i.e., the probability of failure) is below a user-specified bound known as the risk bound. An example problem is to drive a car to a destination as fast as possible while limiting the probability of an accident to 10(exp -7). This framework allows users to trade conservatism against performance by choosing the risk bound. The more risk the user accepts, the better performance they can expect.
Wildfires are an important source of reactive nitrogen species including nitrogen oxides (NOx = NO + NO2) and nitrous acid (HONO), as well as products such as nitric acid (HNO3) and particulate nitrate (p-NO3-). These species have strongly influence air quality and climate. In summer of 2019 (July 25 —August 21), as part of the FIREX-AQ ground mission, we drove ~3000 miles and sampled smoke of different ages in both daytime and nighttime from 5 different wildfires in the western US. Using recently developed methods that have been validated in both laboratory and field settings, we conducted high time resolution collection of NOx, NO2, HONO, HNO3, and p-NO3- for off-line characterization of isotopic composition δ15N, δ18O and Δ17O (=δ17O−0.52 δ18O). δ15N serves as a potential tracer for tracking sources and reactive nitrogen cycling pathways, δ18O and Δ17O provide key information about oxidation pathways (i.e. O3 versus RO2). Our measured δ15N for HONO ranges from -4.9‰ to +5.2‰ and -8‰ to +5.2‰ respectively, in the majority overlapping with our prior lab controlled burning results, which suggests the capability of δ15N for tracing the biomass burning emissions against other sources including vehicular emissions and soil emissions. In addition, our measurements show δ18O and Δ17O for NO2 and HONO vary significantly day vs night, as well as in young smoke vs aged smoke, likely reflecting different oxidizing mechanisms under different smoke conditions. Preliminary results of isotopic signatures of all the above reactive nitrogen species will be presented, and their relationships will be explored to identify wildfire derived reactive nitrogen source signatures and to constrain atmospheric processing pathways (e.g. secondary formation of HONO) for different fires under various smoke conditions depending on fuel types, fire conditions and meteorological conditions.
Here we present a decomposition approach for obtaining good feasible solutions for the security-constrained, alternating-current, optimal power flow (SC-AC-OPF) problem at an industrial scale and under real-world time and computational limits. The approach was designed while preparing and participating in ARPA-E’s Grid Optimization Competition (GOC) Challenge 1. The challenge focused on a near-real-time version of the SC-AC-OPF problem, where a base operating point is optimized, taking into account possible single-element contingencies, after which the system adapts its operating point following the response of automatic frequency droop controllers and voltage regulators. Our solution approach for this problem relies on state-of-the-art nonlinear programming algorithms, and it employs nonconvex relaxations for complementarity constraints, a specialized two-stage decomposition technique with sparse approximations of recourse terms and contingency ranking and prescreening. The paper describes and justifies our approach and outlines the features of its implementation, including functions and derivatives evaluation, warm-starting strategies, and asynchronous parallelism. We discuss the results of the independent benchmark of our approach by ARPA-E’s GOC team in Challenge 1, where it was found to consistently produce high-quality solutions across a wide range of network sizes and difficulty, and conclude by outlining future extensions of the approach.
NASA space communications systems have the challenge of designing SDRs with highly-constrained Size, Weight and Power (SWaP) resources. A study is being conducted to assess the effectiveness of applying the MDA Platform-Independent Model (PIM) and one or more Platform-Specific Models (PSM) specifically to address NASA space domain real-time issues. This paper will summarize our experiences with applying MDA to SDR for Space to model real-time issues. Real-time issues to be examined, measured, and analyzed are: meeting waveform timing requirements and efficiently applying Real-time Operating System (RTOS) scheduling algorithms, applying safety control measures, and SWaP verification. Real-time waveform algorithms benchmarked with the worst case environment conditions under the heaviest workload will drive the SDR for Space real-time PSM design.
This paper describes the work for optimizing the propulsive efficiency of flapping airfoils, i.e., improving the thrust under constraining aerodynamic work during the flapping flights by changing their shape and trajectory of motion with the unsteady discrete adjoint approach. For unsteady problems, it is essential to properly resolving time scales of motion under consideration and it must be compatible with the objective sought after. We include both the instantaneous and time-averaged (periodic) formulations in this study. For the design optimization with shape parameters or motion parameters, the time-averaged objective function is found to be more useful, while the instantaneous one is more suitable for flow control. The instantaneous objective function is operationally straightforward. On the other hand, the time-averaged objective function requires additional steps in the adjoint approach; the unsteady discrete adjoint equations for a periodic flow must be reformulated and the corresponding system of equations solved iteratively. We compare the design results from shape and trajectory optimizations and investigate the physical relevance of design variables to the flapping motion at on- and off-design conditions.
The design and preliminary testing of a system for isolating microgravity sensitive payloads from spacecraft vibrational and impulsive disturbances is discussed. The Microgravity Isolation Mount (MGIM) concept consists of a platform which floats almost freely within a limited volume inside the spacecraft, but which is constrained to follow the spacecraft in the long term by means of very weak springs. The springs are realized magnetically and form part of a six degree of freedom active magnetic suspension system. The latter operates without any physical contact between the spacecraft and the platform itself. Power and data transfer is also performed by contactless means. Specifications are given for the expected level of input disturbances and the tolerable level of platform acceleration. The structural configuration of the mount is discussed and the design of the principal elements, i.e., actuators, sensors, control loops and power/data transfer devices are described. Finally, the construction of a hardware model that is being used to verify the predicted performance of the MGIM is described.
Ozone formation in urban smog is controlled by a complex set of reactions which includes radical production from photochemical processes, catalytic cycles which convert NO to NO2, and termination steps that tie up reactive intermediates in long-lived reservoirs. The reaction OH + NO2 + M -4 HONO2 + M (la) is a key termination step because it transforms two short-lived reactive intermediates, OH and NO2, into relatively long-lived nitric acid. Under certain conditions (low VOC/NOx), ozone production in polluted urban airsheds can be highly sensitive to this reaction, but the rate parameters are not well constrained. This report summarizes the results of new laboratory studies of the OH + NO2 + M reaction including direct determination of the overall rate constant and branching ratio for the two reaction channels under atmospherically relevant conditions.
Cable-Driven Parallel Robots (CDPRs) are highly suitable for automated panelized building retrofits, thanks to their compact footprint and high payload-to-weight ratio. A common CDPR configuration featuring eight cables, where the anchors form a rectangular prism in front of the building facade, offers a large wrench feasible workspace and good control versatility. However, installing upper anchor points requires additional support structures, such as towers or beams, increasing setup complexity and posing logistical challenges in construction settings. To mitigate these challenges, we propose a six-cable CDPR model specifically designed for automated panelized building retrofits. Although the feasible workspace is limited, our analysis shows that the proposed CDPR adequately covers the critical areas required for panel installation. To validate that the six-cable system can effectively transport the end effector to the desired installation pose, we calculated optimal trajectories based on a constrained dynamic model. The simulation results of the six-cable CDPR demonstrate promising potential for automated panelized building retrofits, effectively balancing simplicity, cost-effectiveness, and functionality.
The stability of spinning flexible satellites in a force-free environment was analyzed. The satellite was modeled as a rigid core having attached to it a flexible appendage idealized as a collection of particles (point masses) interconnected by springs. Both Liapunov and Routh-Hurwitz stability procedures are used. In the former, the Hamiltonian of the system, constrained through the angular momentum integral so as to admit complete damping, is used as a testing function. Equations of motion are written using the hybrid coordinate formulation, which readily accepts a modal coordinate transformation ultimately allowing truncation to a level amenable to literal stability analysis. Closed form stability criteria are generated for the first mode of a restricted appendage model lying in a plane containing the system center of mass and orthogonal to the spin axis. The effects of spin on flexible bodies are discussed by considering a very elementary particle model. Control of passively unstable spacecraft is briefly considered.
This work introduces Physics -informed State -space neural network Models (PSMs), a novel solution to achieving real-time optimization, flexibility, and fault tolerance in autonomous systems, particularly in transportdominated systems such as chemical, biomedical, and power plants. Traditional data -driven methods fall short due to a lack of physical constraints like mass conservation; PSMs address this issue by training deep neural networks with sensor data and physics -informing using components' Partial Differential Equations (PDEs), resulting in a physics -constrained, end -to -end differentiable forward dynamics model. Further, through two in silico experiments - a heated channel and a cooling system loop - we demonstrate that PSMs offer a more accurate approach than a purely data -driven model. In the former experiment, PSMs demonstrated significantly lower average root -mean -square errors across test datasets compared to a purely data -driven neural network, with reductions of 44 %, 48 %, and 94 % in predicting pressure, velocity, and temperature, respectively. Beyond accuracy, PSMs demonstrate a compelling multitask capability, making them highly versatile. In this work, we showcase two: supervisory control of a nonlinear system through a sequentially updated state -space representation and the proposal of a diagnostic algorithm using residuals from each of the PDEs. The former demonstrates PSMs' ability to handle constant and time -dependent constraints, while the latter illustrates their value in system diagnostics and fault detection.
The coupled carbon (C) cycle across terrestrial and aquatic environments at the watershed scale has been identified as an important, but poorly constrained component of the global carbon budget. Here, we extended Soil and Water Assessment Tool (SWAT) with coupled riverine particulate organic carbon (POC) and dissolved organic carbon (DOC) modules (referred to as SWAT-C hereafter). Results show that SWAT-C reproduced daily POC and DOC fluxes well in two watersheds in the Northeastern United States. We found that SWAT-C tended to underestimate high flows and peak DOC and POC fluxes. Uncertainty analysis indicated flux uncertainties associated with POC and DOC simulation were larger than those for flow simulation. Sensitive parameters controlling POC and DOC biogeochemical processes were identified along with how these parameters influence mechanisms underlying C cycling. We anticipate that the tool developed and applied here will inform C related ecosystem services in watershed assessment and planning.
The growth of computational power has fueled attempts to automate more of the human role in complex problem solving domains, especially those where system faults have high consequences and where periods of high workload may saturate the performance capacity of human operators. Examples of these domains include flightdecks, space stations, air traffic control, nuclear power operation, ground satellite control rooms, and surgical operating rooms. Automation efforts may have unanticipated effects on human performance, particularly if they increase the workload at peak workload times or change the practitioners' strategies for coping with workload. Smooth and effective changes in automation requires detailed understanding of the congnitive tasks confronting the user: it has been called user centered automation. The introduction of a new computerized technology in a group of hospital operating rooms used for heart surgery was observed. The study revealed how automation, especially 'clumsy automation', effects practitioner work patterns and suggest that clumsy automation constrains users in specific and significant ways. Users tailor both the new system and their tasks in order to accommodate the needs of process and production. The study of this tailoring may prove a powerful tool for exposing previously hidden patterns of user data processing, integration, and decision making which may, in turn, be useful in the design of more effective human-machine systems.