A SIMPLIFIED FINITE ELEMENT MODEL FOR DESIGN OF A RESONANT PLATE
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A nonlinear dynamic model with full flight envelope controller is developed for the propulsion system of a partially turboelectric single-aisle aircraft. The propulsion system model consists of two turbofan engines with a large percentage of power extraction, feeding an electric tail fan for boundary layer ingestion. The dynamic model is compared against an existing steady state design model. An electrical system model using a simple power flow approach is integrated into existing modeling tools used for dynamic simulation of the turbomachinery of the vehicle. In addition to the simple power flow model of the electrical system, a more detailed model is used for comparison at a key vehicle transient flight condition. The controller is a gain scheduled proportional-integral type that is examined throughout the flight envelope for performance metrics such as rise time and operability margins. Potential improvements in efficiency for the vehicle are explored by adjusting the power split between the energy used for thrust by the turbofans and that extracted to supply power to the tail fan. Finally, an operability study of the vehicle is conducted using a 900 nautical mile mission profile for a nominal vehicle configuration, a deteriorated propulsion system at the end of its operating life, and an optimized power schedule with improved efficiency.
This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.
Many spacecraft systems have ambitious objectives that place stringent requirements on control systems. Achievable performance is often limited because of difficulty of obtaining accurate models for flexible space structures. To achieve sufficiently high performance to accomplish mission objectives may require the ability to refine the control design model based on closed-loop test data and tune the controller based on the refined model. A control system design procedure is developed based on mixed H2/H(infinity) optimization to synthesize a set of controllers explicitly trading between nominal performance and robust stability. A homotopy algorithm is presented which generates a trajectory of gains that may be implemented to determine maximum achievable performance for a given model error bound. Examples show that a better balance between robustness and performance is obtained using the mixed H2/H(infinity) design method than either H2 or mu-synthesis control design. A second contribution is a new procedure for closed-loop system identification which refines parameters of a control design model in a canonical realization. Examples demonstrate convergence of the parameter estimation and improved performance realized by using the refined model for controller redesign. These developments result in an effective mechanism for achieving high-performance control of flexible space structures.
Presentation objectives include: a) Overview of the ACES/CNS System Models Design and Integration; b) Configuration Capabilities available for Models and Simulations using ACES with CNS Modeling; c) Descriptions of recently added, Enhanced CNS Simulation Capabilities; and d) General Concepts Ideas that Utilize CNS Modeling to Enhance Concept Evaluations.
Emerging mobility technologies are changing the transportation system landscape. This is especially evident at airports, such as the Dallas-Fort Worth International Airport (DFW). Without careful analysis, these changes could lead to inefficient and costly airport operations. This paper presents a modeling framework that integrates travel mode encoding, demand projection, and microsimulation to enable airports to develop, simulate, and evaluate curbside traffic managements policies and measure their impact. Here, the framework is utilized to analyze several traffic scenarios and policies for DFW: a baseline scenario which represents DFW traffic pattern as observed in 2018 and projected to 2045, a transit network company (TNC) electrification policy, a TNC queuing policy, a policy that increased transit ridership, a bus-only policy which considers the use of only buses inside DFW, an autonomous vehicle (AV) policy which investigates the impact of autonomous vehicle (AV) adoption on airport operations, and an example COVID-19 scenario which models the impact of the COVID19 pandemic. The simulations’ results demonstrate that: increasing the DFW transit ridership postpones the need for airport curbside expansion the most; encouraging shared-mobility with the bus-only policy produces the most savings in curbside congestion delays; automation and electrification for all passenger vehicle trips to/from DFW generates the most saving in fuel consumption and emissions; and uncontrolled AV adoption incurs the highest increase in fuel consumption, delay, and emissions and could require immediate airport capacity extension. Without policy intervention or investment in additional infrastructure capacity, these results predict the current operations would face significant congestion on high demand days starting as early as 2028. While derived in close partnership with DFW, the methodology presented here can be generalized to any airport.
A model inverse design problem is used to investigate the effect of flow discontinuities on the optimization process. The optimization involves finding the cross-sectional area distribution of a duct that produces velocities that closely match a targeted velocity distribution. Quasi-one-dimensional flow theory is used, and the target is chosen to have a shock wave in its distribution. The objective function which quantifies the difference between the targeted and calculated velocity distributions may become non-smooth due to the interaction between the shock and the discretization of the flowfield. This paper offers two techniques to resolve the resulting problems for the optimization algorithms. The first, shock-fitting, involves careful integration of the objective function through the shock wave. The second, coordinate straining with shock penalty, uses a coordinate transformation to align the calculated shock with the target and then adds a penalty proportional to the square of the distance between the shocks. The techniques are tested using several popular sensitivity and optimization methods, including finite-differences, and direct and adjoint discrete sensitivity methods. Two optimization strategies, Gauss-Newton and sequential quadratic programming (SQP), are used to drive the objective function to a minimum.
The simulation development associated with the network models of both the Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) and the Full Service ISDN Satellite (FSIS) architectures is documented. The ISIS Network Model design represents satellite systems like the Advanced Communications Technology Satellite (ACTS) orbiting switch. The FSIS architecture, the ultimate aim of this element of the Satellite Communications Applications Research (SCAR) Program, moves all control and switching functions on-board the next generation ISDN communications satellite. The technical and operational parameters for the advanced ISDN communications satellite design will be obtained from the simulation of ISIS and FSIS engineering software models for their major subsystems. Discrete event simulation experiments will be performed with these models using various traffic scenarios, design parameters, and operational procedures. The data from these simulations will be used to determine the engineering parameters for the advanced ISDN communications satellite.
With anticipated increases in global energy use and their associated emissions, there are many efforts to improve the emissions and efficiency of many industrial processes through waste heat recovery (WHR). To maximize improvements, the heat exchangers in WHR power cycles must be designed and optimized for a given heat source. Meanwhile, additive manufacturing (AM) is a single part manufacturing technique that provides the opportunity to develop unique and complex heat exchanger designs. Consequently, this work centers on the modeling, design, optimization, and testing of AM shell and tube heat exchangers for WHR. Specifically, a modified one-dimensional (1+1-D) and three-dimensional (3-D) heat exchanger models were developed and validated, with the 1+1-D model serving as the basis for design optimization. After modifications to the design to allow for AM, heat exchanger geometry optimizations were completed, targeting increased effectiveness across a range of physical parameters. Of the designs considered, nine were additively manufactured using Ti5553, and then tested using an external heat source and working fluid. Experimentally, the nineteen-tube, zero-baffle heat exchanger displayed the best overall performance, with the effects of dimensional accuracy, surface roughness, and baffles in the other designs also indicated. Next, the experimental results were used as inputs for the 1+1-D model. Although the original model was able to predict fluid outlet temperatures within 5% differences, larger variations in the heat exchanger performance parameters, temperature differences, and pressure drop necessitated optimizing the pressure drop and heat transfer calculations within the model. Thus, the resulting improved model was able to predict the heat transfer rates, heat source temperature difference, and effectiveness within 15% differences, while showing improvements in the pressure drops and working fluid temperature differences. The improved model serves as the foundation for future work to improve the design and performance of AM heat exchangers.
Prototype antenna design and methods of measuring and predicting antenna characteristics when mounted on space shuttle scale models
Study provides basic information for designing models and conducting thermal-dynamic structural tests. Factors considered are development and interpretation of thermal-dynamic structural scaling laws; identification of major problem areas; and presentation of model fabrication, instrumentation, and test procedures.
The lack of integrated design tools for Surface Acoustic Wave (SAW) devices has led us to develop tools for the design, modeling, analysis, and automatic layout generation of SAW devices. These tools enable rapid development of wireless SAW sensors. The tools developed have been designed to integrate into existing Electronic Design Automation (EDA) tools to take advantage of existing 3D modeling, and Finite Element Analysis (FEA). This paper presents the SAW design, modeling, analysis, and automated layout generation tools.
Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.
The model building, development, and testing experience gained during 8 years of operation of the 0.3-m Transonic Cryogenic Tunnel (TCT) is summarized. The summary is divided into four portions: (1) models tested in the 0.3-m TCT's original octagonal test section; (2) models tested in the present two dimensional test section; (3) models tested as a part of tunnel calibration and the development of advanced technology airfoils; and (4) development of a new way to construct two dimensional airfoil models. Design requirements imposed on the models by high Reynolds number testing at cryogenic temperatures are reviewed.
Using meteorological and hydrological measurements taken in and above the central-Amazon-basin tropical forest, calibration of the Sellers et al. (1986) simple biosphere (SiB) model are described. The SiB model is a one-dimensional soil-vegetation-atmosphere model designed for use within GCMs models, representing the vegetation cover by analogy with processes operating within a single representative plant. The experimental systems and the procedures used to obtain field data are described, together with the specification of the physiological parameterization required to provide an average description of data. It was found that some of the existing literature on stomatal behavior for tropical species is inconsistent with the observed behavior of the complete canopy in Amazonia, and that the rainfall interception store of the canopy is considerably smaller than originally specified in the SiB model.
This study investigates the use of H2, p-synthesis, and mixed H2/mu methods to construct full-order controllers and optimized controllers of fixed dimensions. The benchmark problem definition is first extended to include uncertainty within the controller bandwidth in the form of parametric uncertainty representative of uncertainty in the natural frequencies of the design model. The sensitivity of H2 design to unmodelled dynamics and parametric uncertainty is evaluated for a range of controller levels of authority. Next, mu-synthesis methods are applied to design full-order compensators that are robust to both unmodelled dynamics and to parametric uncertainty. Finally, a set of mixed H2/mu compensators are designed which are optimized for a fixed compensator dimension. These mixed norm designs recover the H, design performance levels while providing the same levels of robust stability as the u designs. It is shown that designing with the mixed norm approach permits higher levels of controller authority for which the H, designs are destabilizing. The benchmark problem is that of an active tendon system. The controller designs are all based on the use of acceleration feedback.