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The software for the field interface module (FIM) is designed to fully optimize the hardware capabilities of the FIM. Software routines exist which enable the FIM to monitor data, control components, communicate with an uplink computer, and perform real-time and local self-diagnostics. The FIM program is not dependent upon any particular uplink computer and is adaptable to various applications with a miniumum of modifications.
Man's ability to live and perform useful work in space was demonstrated throughout the history of manned space flight. Current planning envisions a multi-functional space station. Man's unique abilities to respond to the unforeseen and to operate at a level of complexity exceeding any reasonable amount of previous planning distinguish him from present day machines. His limitations, however, include his inherent inability to survive without protection, his limited strength, and his propensity to make mistakes when performing repetitive and monotonous tasks. By contrast, an automated system does routine and delicate tasks, exerts force smoothly and precisely, stores, and recalls large amounts of data, and performs deductive reasoning while maintaining a relative insensitivity to the environment. The establishment of a permanent presence of man in space demands that man and machines be appropriately combined in spaceborne systems. To achieve this optimal combination, research is needed in such diverse fields as artificial intelligence, robotics, behavioral psychology, economics, and human factors engineering.
Progress in the following areas is described: refining altimeter and altimeter crossover measurement models for precise orbit determination and for the solution of the earth's gravity field; performing experiments using altimeter data for the improvement of precise satellite ephemerides; and analyzing an optimal relative data weighting algorithm to combine various data types in the solution of the gravity field.
In the face of numerically superior hostile forces, deployment of individual vehicles to the right place, at the right time, and the ability to plan missions with less conservatism, will become significant force multipliers. Far-field mission planning is one of the enabling technologies that will facilitate force coordination through management of mission timeline, vehicle survivability and fuel constraints. On-board replanning is required to deal responsively with departures from nominal plan execution that result from imperfect knowledge of and temporal variability in the mission environment. The far-field planning problem is posed as a constrained optimization problem and algorithms and structural organization are proposed for the solution.
Pulsed coherent radars' receiving efficiency, eta, is presently investigated as a function of range z on the basis of a theory which relates eta(z) to both the transmitted laser intensity and the point-source receiving efficiency; this efficiency is calculated by a backward method employing the back-propagated local oscillator (BPLO) approach. The theory is applied to the ideal case, in order to study system optimization when both the transmitted and the BPLO fields at the antenna are Gaussian. In the second part of this work, eta(z) is calculated for various conditions of the NOAA/ERL Wave Propagation Laboratory CO2 Doppler lidar; the sensitivity of eta(z) to transmitted laser beam quality, telescope focal setting, telescope power, scanner astigmatism, and system misalignment.
The utility of a recently developed analytical micromechanics model for the response of metal matrix composites under thermal loading is illustrated by comparison with the results generated using the finite-element approach. The model is based on the concentric cylinder assemblage consisting of an arbitrary number of elastic or elastoplastic sublayers with isotropic or orthotropic, temperature-dependent properties. The elastoplastic boundary-value problem of an arbitrarily layered concentric cylinder is solved using the local/global stiffness matrix formulation (originally developed for elastic layered media) and Mendelson's iterative technique of successive elastic solutions. These features of the model facilitate efficient investigation of the effects of various microstructural details, such as functionally graded architectures of interfacial layers, on the evolution of residual stresses during cool down. The available closed-form expressions for the field variables can readily be incorporated into an optimization algorithm in order to efficiently identify optimal configurations of graded interfaces for given applications. Comparison of residual stress distributions after cool down generated using finite-element analysis and the present micromechanics model for four composite systems with substantially different temperature-dependent elastic, plastic, and thermal properties illustrates the efficacy of the developed analytical scheme.
Modified boundary conditions (MBC) and a multilayer approach (MA) are proposed as fast and efficient numerical methods for the design of 1D photonic structures with rough interfaces. These methods are applicable for the structures, composed of materials with arbitrary permittivity tensor. MBC and MA are numerically validated on different types of interface roughness and permittivities of the constituent materials. The proposed methods can be combined with the 4x4 scattering matrix method as a field solver and an evolutionary strategy as an optimizer. The resulted optimization procedure is fast, accurate, numerically stable and can be used to design structures for various applications.
The application of Calorimetric Low-Temperature Detectors (CLTDs) has been proposed at the Heavy-Ion TRAP facility HITRAP which is currently being installed at the Helmholtz Research Center for Heavy Ion Research GSI. This cold ion trap setup will allow the investigation of X-rays from ions practically at rest, for which the excellent energy resolution of CLTDs can be used to its full advantage. However, the relatively low intensities at HITRAP demand larger solid angles and an optimized cryogenic setup. The influence of external magnetic fields has to be taken into account. CLTDs will also be a substantial part of the instrumental equipment at the future Facility for Antiproton and Heavy Ion Research (FAIR), for which a wide variety of high-precision X-ray spectroscopy experiments has been proposed. This contribution will give an overview on the chances and challenges for the application of CLTDs at HITRAP as well as perspectives for future experiments at the FAIR facility.
The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.
The Space Superhighway is a future space infrastructure concept intended to support civil, commercial, and national security space interests by providing In-Space Servicing, Assembly, and Manufacturing (ISAM) services across low Earth orbit (LEO), geosynchronous orbit (GEO), and cislunar space. This concept was originally developed by an interagency working group and commissioned by the Executive Office of the President. The Space Superhighway is comprised of three primary components: regional hubs, a sustainable transportation network, and Earth-to-orbit logistics. This study establishes methods which may be used to quantify the cost-savings from use of the Space Superhighway infrastructure and interrogates the effects of the use of this logistics network on a specific use case – removal of 26 pieces of large space debris within LEO. Through application of the established methods and assuming an emplaced Space Superhighway infrastructure with no cost implications related to deployment of infrastructure-related spacecraft, this study found that the cost to use an established Space Superhighway infrastructure to remove the targeted debris may be cheaper than removal of the targeted debris through traditional methods when the ΔV between a regional hub hosting propellant and the debris field is less than 1500 m/s. Through determining optimized locations of regional hubs within LEO, this study estimates that such a ΔV is within expectations for a LEO environment supported by a fully evolved Space Superhighway logistics infrastructure. This study provides a blueprint for future Space Superhighway value proposition studies for other use cases which, when combined, may provide the ultimate benefit and justification for the proliferation of an interconnected Space Superhighway.
The Space Superhighway is a future space infrastructure concept intended to support civil, commercial, and national security space interests by providing In-Space Servicing, Assembly, and Manufacturing (ISAM) services across low Earth orbit (LEO), geosynchronous orbit (GEO), and cislunar space. This concept was originally developed by an interagency working group and commissioned by the Executive Office of the President. The Space Superhighway is comprised of three primary components: regional hubs, a sustainable transportation network, and Earth-to-orbit logistics. This study establishes methods which may be used to quantify the cost-savings from use of the Space Superhighway infrastructure and interrogates the effects of the use of this logistics network on a specific use case – removal of 26 pieces of large space debris within LEO. Through application of the established methods and assuming an emplaced Space Superhighway infrastructure with no cost implications related to deployment of infrastructure-related spacecraft, this study found that the cost to use an established Space Superhighway infrastructure to remove the targeted debris may be cheaper than removal of the targeted debris through traditional methods when the ΔV between a regional hub hosting propellant and the debris field is less than 1500 m/s. Through determining optimized locations of regional hubs within LEO, this study estimates that such a ΔV is within expectations for a LEO environment supported by a fully evolved Space Superhighway logistics infrastructure. This study provides a blueprint for future Space Superhighway value proposition studies for other use cases which, when combined, may provide the ultimate benefit and justification for the proliferation of an interconnected Space Superhighway.
Accurate modeling of coolant airflows, which form protective films over turbine blades, is essential for designing fuel-efficient and environmentally sustainable gas turbine engines. Excessive coolant reduces thermal efficiency, while insufficient coolant leads to blade overheating and causes damage. Therefore, precise prediction of flow field interactions with cooling air is critical for optimizing turbine performance. This study numerically investigates the cooling effectiveness of purge and film cooling flows within a high-pressure turbine (HPT) rotor using Large Eddy Simulation (LES). The study utilizes NASA Glenn Research Center’s Glenn-HT solver. The simulation models ethe conditions of the Penn State University START rotating rig. A high-fidelity structured mesh comprising up to 800 million cells is employed to resolve high-Reynolds number flow (Re ≈ 350,000) and to capture intricate secondary flow structures, including tip leakage and purge-induced vortices. Film cooling effectiveness computations are highly sensitive to boundary conditions at the cooling holes and to grid resolution. Even with well-resolved grids and included plena, strong mixing challenges traditional eddy viscosity models. To address this, a simplified configuration is simulated: a truncated row of shaped holes on the suction side near the leading edge and a row on the pressure side, both fed from internal plena while the purge slot and tip clearance are also modeled. Two isothermal LES cases are conducted at two distinct wall temperatures, which yield the adiabatic wall temperature and the heat transfer coefficient. The definition and means of computation of the effectiveness is discussed in this paper. The simulations reveal detailed three-dimensional unsteady flow features, including coherent vortical structures and secondary flows originating from the purge cavity. Film cooling effectiveness and Nusselt number distributions are presented for both the blade surface and tip, highlighting regions of elevated heat transfer and complex thermal behavior. These findings underscore the importance of high-resolution LES and realistic boundary conditions in capturing the dynamics of purge and film cooling, offering valuable insights for improving turbine blade design and thermal management strategies.
Accurate modeling of coolant airflows, which form protective films over turbine blades, is essential for designing fuel-efficient and environmentally sustainable gas turbine engines. Excessive coolant reduces thermal efficiency, while insufficient coolant leads to blade overheating and causes damage. Therefore, precise prediction of flow field interactions with cooling air is critical for optimizing turbine performance. This study numerically investigates the cooling effectiveness of purge and film cooling flows within a high-pressure turbine (HPT) rotor using Large Eddy Simulation (LES). The study utilizes NASA Glenn Research Center’s Glenn-HT solver. The simulation models ethe conditions of the Penn State University START rotating rig. A high-fidelity structured mesh comprising up to 800 million cells is employed to resolve high-Reynolds number flow (Re ≈ 350,000) and to capture intricate secondary flow structures, including tip leakage and purge-induced vortices. Film cooling effectiveness computations are highly sensitive to boundary conditions at the cooling holes and to grid resolution. Even with well-resolved grids and included plena, strong mixing challenges traditional eddy viscosity models. To address this, a simplified configuration is simulated: a truncated row of shaped holes on the suction side near the leading edge and a row on the pressure side, both fed from internal plena while the purge slot and tip clearance are also modeled. Two isothermal LES cases are conducted at two distinct wall temperatures, which yield the adiabatic wall temperature and the heat transfer coefficient. The definition and means of computation of the effectiveness is discussed in this paper. The simulations reveal detailed three-dimensional unsteady flow features, including coherent vortical structures and secondary flows originating from the purge cavity. Film cooling effectiveness and Nusselt number distributions are presented for both the blade surface and tip, highlighting regions of elevated heat transfer and complex thermal behavior. These findings underscore the importance of high-resolution LES and realistic boundary conditions in capturing the dynamics of purge and film cooling, offering valuable insights for improving turbine blade design and thermal management strategies.
PERLE (Powerful Energy Recovery LINAC for Experiment) is a high-power Energy Recovery LINAC (ERL) facility with 20 mA beam current and beam energy from 250 MeV to 500 MeV featuring three passes through two cryomodules. It is a hub for validation of the ERL technology development towards future energy and intensity frontier machines. Design challenges of PERLE and its beam parameters make it a test-bed to validate multi-turn high current ERL operation for the LHeC. It will be the first ERL for some pioneering experiment of the eN interaction with radioactive nuclei. In this work, design and optimization of the commutational magnet (B-com) used to spread/combine the three beams and one series of the quadrupole magnet is discussed. It gives the design parameters including: yoke geometry, pole profile, and material, and calculation of the excitation current needed to drive the magnet, the coil parameters and the number of turns. The B-com magnet is optimized for a 30° bending angle with magnetic field of 0.88 T along the magnet length and a harmonic content of 0.036%. The quadrupole magnet is designed for a gradient field of 34.15 T/m and experiences saturation above this value. Further studies to avoid saturation and achieve the maximum gradient of 44.1 T/m required by the beam dynamics is undergoing.
We use the new simulation capabilities of the extended-magnetohydrodynamic (MHD) code, M3D-C1, to investigate the nonlinear MHD properties of a reactor-scale quasisymmetric stellarator equilibrium. Our model captures the self-consistent evolution of the magnetic field, temperature, density, and flow profiles without imposing restrictions on the structure of the first. We include the effects of resistivity using a realistic temperature-dependent Spitzer model, along with a model for heat transport that captures the key physical characteristic, namely, strongly anisotropic diffusion in directions perpendicular and parallel to the magnetic field. We consider a quasi-axisymmetric, finite-pressure equilibrium that was optimized for self-consistent bootstrap current, quasi-symmetry, and energetic particle confinement. Our assessment finds that the equilibrium is highly unstable to interchange-like pressure-driven instabilities near the plasma edge. The initially unstable modes rapidly destabilize other modes in the direction of the N-fold rotational symmetry (toroidal, in this case). For this equilibrium, N = 2, meaning destabilization of a large number of even-numbered toroidal Fourier modes. Thus, field-periodicity is likely to be an important factor in the nonlinear MHD stability characteristics of optimized stellarators.
Extensive experimental research on high-pressure spray has been conducted for decades to deepen our understanding and optimize its use in transportation, aviation, and propulsion applications; however, the near-field and in-nozzle flow characteristics are not fully understood. Dense near-field spray is among the most challenging diagnostic tasks since light is severely scattered and diffused by the liquid droplets and columns. In this work, the near-field spray and in-nozzle flow characteristics of an aeration nozzle at elevated pressures were characterized by neutron radiography imaging at the Oak Ridge National Laboratory High Flux Isotope Reactor. Neutron imaging benefits via strong penetration depths for some metals (i.e., aluminum, lead, and steel) and is sufficiently sensitive to detection of light elements, especially for hydrogen-based molecules, due to the large incoherent scattering cross section of neutrons. Both two-dimensional snapshots of the near-field spray and a three-dimensional tomographic scan of the nozzle geometry and in-nozzle water were obtained. This work provides new quantitative characterization of practical metal nozzle geometry for accurate boundary conditions, internal flow patterns inside the nozzle, and high-pressure spray flows. In conclusion, the findings may be used to improve performance and operating conditions of transportation vehicles and propulsion systems.
Abstract. Phase correlation (PC) is a well-known method for estimating cloud motion vectors (CMVs) from infrared and visible spectrum images. Commonly, phase shift is computed in the small blocks of the images using the fast Fourier transform. In this study, we investigate the performance and the stability of the blockwise PC method by changing the block size, the frame interval, and combinations of red, green, and blue (RGB) channels from the total sky imager (TSI) at the United States Atmospheric Radiation Measurement user facility's Southern Great Plains site. We find that shorter frame intervals, followed by larger block sizes, are responsible for stable estimates of the CMV, as suggested by the higher autocorrelations. The choice of RGB channels has a limited effect on the quality of CMVs, and the red and the grayscale images are marginally more reliable than the other combinations during rapidly evolving low-level clouds. The stability of CMVs was tested at different image resolutions with an implementation of the optimized algorithm on the Sage cyberinfrastructure test bed. We find that doubling the frame rate outperforms quadrupling the image resolution in achieving CMV stability. The correlations of CMVs with the wind data are significant in the range of 0.38–0.59 with a 95 % confidence interval, despite the uncertainties and limitations of both datasets. A comparison of the PC method with constructed data and the optical flow method suggests that the post-processing of the vector field has a significant effect on the quality of the CMV. The raindrop-contaminated images can be identified by the rotation of the TSI mirror in the motion field. The results of this study are critical to optimizing algorithms for edge-computing sensor systems.
Long-baseline atom interferometers such as the Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100) require stringent control and continuous characterization of background magnetic fields and spatial gradients to prevent systemic phase shifts that mimic ultralight dark matter or gravitational wave signatures. Because direct sensor placement within the ultra-high vacuum beam pipe is infeasible, in-situ magnetic field monitoring relies on external sensor arrays situated in the surrounding annular region. This work demonstrates a field reconstruction framework for a 5.3-meter MAGIS-100 modular section using finite-element Opera simulations. Transverse magnetic fields are expanded using a cylindrical multipole framework as informed by Fermilab’s Muon g-2 experiment, with magnetometer array configurations optimized via Fisher information matrix D-optimality. Inverting external sensor readings through a Gauss-Newton scheme recovers interior tube fields across distinct axial positions. In the discontinuity-averse uniform region (slice pair P4), the model achieves sub-noise-floor performance with a cross-validated root-mean-square error (RMSE) of $6.7227 \times 10^{-4}\text{ A/m}$ ($0.845\times$ sensor noise floor) and an interior field coefficient of variation of $1.71\%$. An elbow criterion in the Fisher bounds establishes $n_{\text{max}} = 2$ as the optimal multipole truncation order to prevent noise amplification from over-parameterization, with $n_{\text{max}} = 3$ (sextupole) order chosen for analysis to demonstrate further complexity and cross-pair comparison. Furthermore, analytical differentiation of the fitted multipole coefficients yields dense spatial maps of the transverse Jacobian gradient matrix $\nabla \mathbf{H}$ along with propagated $1\sigma$ uncertainty bounds across the beam region ($r \le 2.75\text{ in}$). This operational framework confirms that external magnetometer arrays can reliably monitor magnetic field uniformity and spatial gradients along the 100-meter flight path given appropriate sampling for any complexity order.