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An Agent-Based Model for Analyzing Control Policies and the Dynamic Service-Time Performance of a Capacity-Constrained Air Traffic Management Facility
Simple agent-based models may be useful for investigating air traffic control strategies as a precursory screening for more costly, higher fidelity simulation. Of concern is the ability of the models to capture the essence of the system and provide insight into system behavior in a timely manner and without breaking the bank. The method is put to the test with the development of a model to address situations where capacity is overburdened and potential for propagation of the resultant delay though later flights is possible via flight dependencies. The resultant model includes primitive representations of principal air traffic system attributes, namely system capacity, demand, airline schedules and strategy, and aircraft capability. It affords a venue to explore their interdependence in a time-dependent, dynamic system simulation. The scope of the research question and the carefully-chosen modeling fidelity did allow for the development of an agent-based model in short order. The model predicted non-linear behavior given certain initial conditions and system control strategies. Additionally, a combination of the model and dimensionless techniques borrowed from fluid systems was demonstrated that can predict the system s dynamic behavior across a wide range of parametric settings.
Controller design via structural reduced modeling by FETM
The Finite Element - Transfer Matrix (FETM) method has been developed to reduce the computations involved in analysis of structures. This widely accepted method, however, has certain limitations, and does not directly produce reduced models for control design. To overcome these shortcomings, a modification of FETM method has been developed. The modified FETM method easily produces reduced models that are tailored toward subsequent control design. Other features of this method are its ability to: (1) extract open loop frequencies and mode shapes with less computations, (2) overcome limitations of the original FETM method, and (3) simplify the procedures for output feedback, constrained compensation, and decentralized control. This semi annual report presents the development of the modified FETM, and through an example, illustrates its applicability to an output feedback and a decentralized control design.
Libration Orbit Mission Design: Applications of Numerical & Dynamical Methods
Sun-Earth libration point orbits serve as excellent locations for scientific investigations. These orbits are often selected to minimize environmental disturbances and maximize observing efficiency. Trajectory design in support of libration orbits is ever more challenging as more complex missions are envisioned in the next decade. Trajectory design software must be further enabled to incorporate better understanding of the libration orbit solution space and thus improve the efficiency and expand the capabilities of current approaches. The Goddard Space Flight Center (GSFC) is currently supporting multiple libration missions. This end-to-end support consists of mission operations, trajectory design, and control. It also includes algorithm and software development. The recently launched Microwave Anisotropy Probe (MAP) and upcoming James Webb Space Telescope (JWST) and Constellation-X missions are examples of the use of improved numerical methods for attaining constrained orbital parameters and controlling their dynamical evolution at the collinear libration points. This paper presents a history of libration point missions, a brief description of the numerical and dynamical design techniques including software used, and a sample of future GSFC mission designs.
Controller design via structural reduced modeling by FETM
The Finite Element-Transfer Matrix (FETM) method has been developed to reduce the computations involved in analysis of structures. This widely accepted method, however, has certain limitations, and does not address the issues of control design. To overcome these, a modification of the FETM method has been developed. The new method easily produces reduced models tailored toward subsequent control design. Other features of this method are its ability to: (1) extract open loop frequencies and mode shapes with less computations, (2) overcome limitations of the original FETM method, and (3) simplify the design procedures for output feedback, constrained compensation, and decentralized control. This report presents the development of the new method, generation of reduced models by this method, their properties, and the role of these reduced models in control design. Examples are included to illustrate the methodology.
A primer on criticality safety
Criticality is the state of a nuclear chain reacting medium when the chain reaction is just self-sustaining (or critical). Criticality is dependent on nine interrelated parameters. Moreover, we design criticality safety controls in order to constrain these parameters to minimize fissions and maximize neutron leakage and absorption in other materials, which makes criticality more difficult or impossible to achieve. We present the consequences of criticality accidents are discussed, the nine interrelated parameters that combine to affect criticality are described, and criticality safety controls used to minimize the likelihood of a criticality accident are presented.
Searching for an optimal control in the presence of saddles on the quantum-mechanical observable landscape
The broad success of theoretical and experimental quantum optimal control is intimately connected to the topology of the underlying control landscape. For several common quantum control goals, including the maximization of an observable expectation value, the landscape has been shown to lack local optima if three assumptions are satisfied: (i) the quantum system is controllable, (ii) the Jacobian of the map from the control field to the evolution operator is full rank, and (iii) the control field is not constrained. In the case of the observable objective, this favorable analysis shows that the associated landscape also contains saddles, i.e., critical points that are not local suboptimal extrema. In this paper, we investigate whether the presence of these saddles affects the trajectories of gradient-based searches for an optimal control. We show through simulations that both the detailed topology of the control landscape and the parameters of the system Hamiltonian influence whether the searches are attracted to a saddle. For some circumstances with a special initial state and target observable, optimizations may approach a saddle very closely, reducing the efficiency of the gradient algorithm. Encounters with such attractive saddles are found to be quite rare. Neither the presence of a large number of saddles on the control landscape nor a large number of system states increases the likelihood that a search will closely approach a saddle. Finally, even for applications that encounter a saddle, well-designed gradient searches with carefully chosen algorithmic parameters will readily locate optimal controls.
Measurement of the $\bar ν_μ-$Hydrogen Charged-Current Quasi-Elastic Cross Section using the NOvA Near Detector
We report a measurement of the total cross section for muon antineutrino charged-current quasi-elastic scattering on hydrogen, $\bar ν_μ{\rm H} \to μ^+ n$, in the NOvA near detector using a $1.2\times10^{21}$ proton-on-target exposure in the NuMI beam. A selection based on topological and kinematic constraints yields 35,509 signal events in the hydrogen-rich ($10.8\%$) detector, providing the highest statistics of (anti)neutrino--hydrogen interactions measured to date. Backgrounds from (anti)neutrino interactions on heavier nuclei are constrained using dedicated data control samples, significantly reducing the related systematic uncertainties. We obtain a value $σ(\bar ν_μ{\rm H} \to μ^+ n) = 0.538 \pm 0.009 ({\rm stat}) \pm 0.010 ({\rm syst}) \pm0.055 ({\rm flux}) \times 10^{-38}$ cm$^2$ for the total cross section at an average energy of 1.9 GeV, the most precise total cross-section measurement of this process to date. The combined statistical and non-flux systematic uncertainty is more than four times smaller than the flux uncertainty, allowing a future use of this measurement to constrain the absolute $\bar ν_μ$ flux.
Measurement of the $\bar ν_μ-$Hydrogen Charged-Current Quasi-Elastic Cross Section using the NOvA Near Detector
We report a measurement of the total cross section for muon antineutrino charged-current quasi-elastic scattering on hydrogen, $\bar ν_μ{\rm H} \to μ^+ n$, in the NOvA near detector using a $1.2\times10^{21}$ proton-on-target exposure in the NuMI beam. A selection based on topological and kinematic constraints yields 35,509 signal events in the hydrogen-rich ($10.8\%$) detector, providing the highest statistics of (anti)neutrino--hydrogen interactions measured to date. Backgrounds from (anti)neutrino interactions on heavier nuclei are constrained using dedicated data control samples, significantly reducing the related systematic uncertainties. We obtain a value $σ(\bar ν_μ{\rm H} \to μ^+ n) = 0.538 \pm 0.009 ({\rm stat}) \pm 0.010 ({\rm syst}) \pm0.055 ({\rm flux}) \times 10^{-38}$ cm$^2$ for the total cross section at an average energy of 1.9 GeV, the most precise total cross-section measurement of this process to date. The combined statistical and non-flux systematic uncertainty is more than four times smaller than the flux uncertainty, allowing a future use of this measurement to constrain the absolute $\bar ν_μ$ flux.
Tradeoff methods in multiobjective insensitive design of airplane control systems
The latest results of an ongoing study of computer-aided design of airplane control systems are given. Constrained minimization algorithms are used, with the design objectives in the constraint vector. The concept of Pareto optimiality is briefly reviewed. It is shown how an experienced designer can use it to find designs which are well-balanced in all objectives. Then the problem of finding designs which are insensitive to uncertainty in system parameters are discussed, introducing a probabilistic vector definition of sensitivity which is consistent with the deterministic Pareto optimal problem. Insensitivity is important in any practical design, but it is particularly important in the design of feedback control systems, since it is considered to be the most important distinctive property of feedback control. Methods of tradeoff between deterministic and stochastic-insensitive (SI) design are described, and tradeoff design results are presented for the example of the a Shuttle lateral stability augmentation system. This example is used because careful studies have been made of the uncertainty in Shuttle aerodynamics. Finally, since accurate statistics of uncertain parameters are usually not available, the effects of crude statistical models on SI designs are examined.
Optimal Control of Differentially Private EV Charging: A Scalable Learning Approach Under Uncertainty
Internet of Things (IoT)-enabled electric vehicles (IoEVs) enable intelligent charging coordination that accounts for grid congestion. However, increased data exchange raises privacy concerns, as charging patterns can reveal sensitive driver behavior to grid operators. Here, we propose a differentially private (DP) EV charging framework that enables coordinated control while protecting driver data with theoretical privacy guarantees. Nevertheless, integrating DP inevitably introduces uncertainty into the control strategy for EVs, which can lead to infeasible solutions. To tackle this challenge, we develop a feasible and scalable control algorithm based on constrained reinforcement learning (CRL) and convex hulls. While our framework is designed to handle the uncertainty introduced by DP, it is general and also applicable to other sources of uncertainty in EV charging, such as the stochastic nature of driver behavior and renewable variability. This ensures feasible and privacy-preserving coordination of EV charging at scale. Our method constructs convex hulls within the action space to guarantee feasibility under stochastic constraints and incorporates constraint reduction techniques to improve scalability. Case studies based on IEEE benchmark systems demonstrate that the proposed approach effectively balances feasibility under uncertainty, scalability, and privacy in large-scale EV charging control.
Dynamic interface rearrangement in LaFeO 3 / n - SrTiO 3 heterojunctions
Thin-film synthesis methods that have developed over the past decades have unlocked emergent interface properties ranging from conductivity to ferroelectricity. However, our attempts to exercise precise control over interfaces are constrained by a limited understanding of growth pathways and kinetics. In this paper, we demonstrate that shuttered molecular beam epitaxy induces rearrangements of atomic planes at a polar/nonpolar junction of LaFeO 3 (LFO)/n-SrTiO 3 (STO) depending on the substrate termination. Surface characterization confirms that substrates with two different (TiO 2 and SrO) terminations were prepared prior to LFO deposition; however, local electron-energy-loss spectroscopy measurements of the final heterojunctions show a predominantly LaO/TiO 2 interfacial junction in both cases. Ab initio simulations suggest that the interfaces can be stabilized by trapping extra oxygen (in LaO/TiO 2 ) and forming oxygen vacancies (in FeO 2 /SrO), which points to different growth kinetics in each case and may explain the apparent disappearance of the FeO 2 /SrO interface. Finally, we conclude that judicious control of deposition time scales can be used to modify growth pathways, opening new avenues to control the structure and properties of interfacial systems.
Evaluation of a Candidate Trace Contaminant Control Subsystem Architecture: The High Velocity, Low Aspect Ratio (HVLA) Adsorption Process
Traditional gas-phase trace contaminant control adsorption process flow is constrained as required to maintain high contaminant single-pass adsorption efficiency. Specifically, the bed superficial velocity is controlled to limit the adsorption mass-transfer zone length relative to the physical adsorption bed; this is aided by traditional high-aspect ratio bed design. Through operation in this manner, most contaminants, including those with relatively high potential energy are readily adsorbed. A consequence of this operational approach, however, is a limited available operational flow margin. By considering a paradigm shift in adsorption architecture design and operations, in which flows of high superficial velocity are treated by low-aspect ratio sorbent beds, the range of well-adsorbed contaminants becomes limited, but the process flow is increased such that contaminant leaks or emerging contaminants of interest may be effectively controlled. To this end, the high velocity, low aspect ratio (HVLA) adsorption process architecture was demonstrated against a trace contaminant load representative of the International Space Station atmosphere. Two HVLA concept packaging designs (linear flow and radial flow) were tested. The performance of each design was evaluated and compared against computer simulation. Utilizing the HVLA process, long and sustained control of heavy organic contaminants was demonstrated.
The design of multirate digital control systems
The successive loop closures synthesis method is the only method for multirate (MR) synthesis in common use. A new method for MR synthesis is introduced which requires a gradient-search solution to a constrained optimization problem. Some advantages of this method are that the control laws for all control loops are synthesized simultaneously, taking full advantage of all cross-coupling effects, and that simple, low-order compensator structures are easily accomodated. The algorithm and associated computer program for solving the constrained optimization problem are described. The successive loop closures , optimal control, and constrained optimization synthesis methods are applied to two example design problems. A series of compensator pairs are synthesized for each example problem. The succesive loop closure, optimal control, and constrained optimization synthesis methods are compared, in the context of the two design problems.
Ionic Liquid-Mediated Scanning Probe Electro-Oxidative Lithography as a Novel Tool for Engineering Functional Oxide Micro- and Nano-Architectures
Functional oxides have extensively been investigated as a promising class of materials in a broad range of innovative applications. Harnessing the novel properties of functional oxides in micro- to nano-scale applications hinges on establishing advanced fabrication and manufacturing techniques able to synthesize these materials in an accurate and reliable manner. Oxidative scanning probe lithography (o-SPL), an atomic force microscopy (AFM) technique based on anodic oxidation at the water meniscus formed at the tip/substrate contact, not only combines the advantages of both “top-down” and “bottom-up” fabrication approaches, but also offers the possibility of fabricating oxide nanomaterials with high patterning accuracy. While the use of self-assembled monolayers (SAMs) broadened the application of o-SPL, significant challenges have emerged owing to the relatively limited number of SAM/solid surface combinations that can be employed for o-SPL, which constrains the ability to control the chemistry and structure of oxides formed by o-SPL. Here, in this work, a new o-SPL technique that utilizes room-temperature ionic liquids (RTILs) as the functionalizing material to mediate the electrochemistry at AFM tip/substrate contacts is reported. The results show that the new IL-mediated o-SPL (IL-o-SPL) approach allows sub-100 nm oxide features to be patterned on a model solid surface, namely steel, with an initiation voltage as low as -2 V. Moreover, this approach enables high tunability of both the chemical state and morphology of the patterned iron oxide structures. Owing to the high chemical compatibility of ILs, which derives from the possibility of synthesizing ILs able to adsorb on a wide variety of solid surfaces, IL-o-SPL can be extended to other material surfaces and provide the opportunity to accurately tailor the chemistry, morphology, and electronic properties within nanoscale domains, thus opening new pathways to the development of novel micro- and nano-architectures for advanced integrated devices.
Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis
Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.
Organic Matter Remineralization Predominates Phosphorus Cycling in the Mid-Bay Sediments in the Chesapeake Bay
The Chesapeake Bay, the largest and most productive estuary in the US, suffers from varying degrees of water quality issues fueled by both point and non–point source nutrient sources. Restoration of the bay is complicated by the multitude of nutrient sources, their variable inputs and hydrological conditions, and complex interacting factors including climate forcing. These complexities not only restrict formulation of effective restoration plans but also open up debates on accountability issues with nutrient loading. A detailed understanding of sediment phosphorus (P) dynamics enables one to identify the exchange of dissolved constituents across the sediment- water interface and aid to better constrain mechanisms and processes controlling the coupling between the sediments and the overlying waters. Here we used phosphate oxygen isotope ratios (δ18Op) in concert with sediment chemistry, XRD, and Mössbauer spectroscopy on the sediment retrieved from an organic rich, sulfidic site in the meso-haline portion of the mid-bay to identify sources and pathway of sedimentary P cycling and to infer potential feedback effect on bottom water hypoxia and surface water eutrophication. Isotope data indicate that the regeneration of inorganic P from organic matter degradation (remineralization) is the predominant, if not sole, pathway for authigenic P precipitation in the mid-bay sediments. We interpret that the excess inorganic P generated by remineralization should have overwhelmed any bottom-water and/or pore-water P derived from other sources or biogeochemical processes and exceeded saturation with respect to authigenic P precipitation. It is the first research that identifies the predominance of remineralization pathway against remobilization (coupled Fe-P cycling) pathway in the Chesapeake Bay. Therefore, these results are expected to have significant implications for the current understanding of P cycling and benthic-pelagic coupling in the bay, particularly on the source and pathway of P that sustains hypoxia and supports phytoplankton growth in the surface water.
Measurement of 𝑑 2 𝜎/𝑑|$\vec{q}$|𝑑𝐸 avail in charged current 𝜈 𝜇 -nucleus interactions at ⟨𝐸 𝜈 ⟩=1.86 GeV using the NOvA Near Detector
Double- and single-differential cross sections for inclusive charged-current 𝜈 𝜇 -nucleus scattering are reported for the kinematic domain 0 to 2 GeV/𝑐 in three-momentum transfer and 0 to 2 GeV in available energy, at a mean 𝜈 𝜇 energy of 1.86 GeV. The measurements are based on an estimated 995,760 𝜈 𝜇 charged-current (CC) interactions in the scintillator medium of the NOvA Near Detector. The subdomain populated by 2-particle-2-hole (2p2h) reactions is identified by the cross section excess relative to predictions for 𝜈 𝜇 -nucleus scattering that are constrained by a data control sample. Models for 2-particle-2-hole processes are rated by 𝜒 2 comparisons of the predicted-versus-measured 𝜈 𝜇 CC inclusive cross section over the full phase space and in the restricted subdomain. Shortfalls are observed in neutrino generator predictions obtained using the theory-based València and SuSAv2 2p2h models.