Nominal Design Research Articles

Fuel burn evaluation of a transonic strut-braced-wing regional aircraft through multipoint aerodynamic optimisation

AbstractThis paper presents a relative fuel burn evaluation of the transonic strut-braced-wing configuration for the regional aircraft class in comparison to an equivalent conventional tube-and-wing aircraft. This is accomplished through multipoint aerodynamic shape optimisation based on the Reynolds-averaged Navier-Stokes equations. Aircraft concepts are first developed through low-order multidisciplinary design optimisation based on the design missions and top-level aircraft requirements of the Embraer E190-E2. High-fidelity aerodynamic shape shape optimisation is then applied to wing–body–tail models of each aircraft, with the objective of minimising the weighted-average cruise drag over a five-point operating envelope that includes the nominal design point, design points at $\pm 10\%$ nominal $C_L$ at Mach 0.78, and two high-speed cruise points at Mach 0.81. Design variables include angle-of-attack, wing (and strut) twist and section shape degrees of freedom, and horizontal tail incidence, while nonlinear constraints include constant lift, zero pitching moment, minimum wing and strut volume, and minimum maximum thickness-to-chord ratios. Results show that the multipoint optimised strut-braced wing maintains similar features to those of the single-point optimum, and compromises on-design performance by only two drag counts to achieve up to 11.6% reductions in drag at the off-design conditions. Introducing low-order estimates for approximating full aircraft performance, results indicate that the multipoint optimised strut-braced-wing regional jet offers a 13.1% improvement in cruise lift-to-drag ratio and a 7.8% reduction in block fuel over a 500nmi nominal mission when compared to the similarly optimised Embraer E190-E2-like conventional tube-and-wing aircraft.

Development of An Open-Source Computational Tool for the Generation of Deviated Point Clouds from Nominal Models

Design for dimensional control refers to the engineering field concerned with variation management in different stages of product development. One of the key elements within the framework of design for dimensional control is the effective use of computational techniques for assisting the designer in defining the dimensional tolerances of mechanical parts. Despite the existence of commercial suites for computer-aided tolerancing, in general, they cannot be afforded by small businesses such as job shops and measurement service providers or be used in engineering courses in emerging economies. To bridge this gap, an open-source computational tool has been developed to assist the user with the specification of dimensional and geometrical controls. The proposed tool generates a point cloud from the nominal computer-aided design (CAD) model of the part and applies known virtual deviations to that original point cloud. Based on the modified/deviated point cloud, the user can perform virtual what-if analysis and improve the tolerancing process. This paper describes the implementation of the proposed method and presents the results of preliminary tolerance studies of some real components of the Sirius particle accelerator.

Comprehensive Surrogate-Based Optimization of Lightweight Composite Manufacturing

The problem of holistic manufacturing optimization in lightweight composite applications is considered. The composite manufacturing optimization problem is explored from a holistic perspective that integrates the material constitutive parameters at different scales with the corresponding physics at every processing phase. To efficiently solve the manufacturing optimization problem in high dimensions, a physics-informed neural network surrogate is developed based on the governing first-principles physics. Focus is placed on training a neural network model that spans across all the different scales and physics at each manufacturing phase of the lightweight composite problem such that subsequent optimization results reflect the integrated, multiscale, and multiphysical aspects of the system. A holistic manufacturing optimization paradigm is formulated to discover optimal design vectors embedded in a parameter space of around 70 dimensions. Various objective functions that reflect different design preferences in the manufacturing problem are explored. In one optimization formulation, the final weight (i.e., density) of the composite design is reduced by 8.9% with respect to the nominal design. An accurate and efficient manufacturing optimization paradigm for composites is essential for lightweight and ultralightweight applications, whereby any weight savings in the composite structure translate into increased system efficiency.

One-Dimensional Optimization Design of Supercritical Carbon Dioxide Radial Inflow Turbine and Performance Analysis under Off-Design Conditions

In the present study, the one-dimensional optimization design and the performance analysis based on a three-dimensional model were performed for a 2.1 MW supercritical carbon dioxide radial inflow turbine. Firstly, an in-house code was developed with MATLAB language for one-dimensional optimization design to maximize the total-to-static efficiency. Then, the three-dimensional radial inflow turbine model was constructed based on the one-dimensional optimization design result. Finally, the flow field and the aerodynamic performance were studied using the commercial software NUMECA. It is shown that the total-to-static efficiency obtained from three-dimensional simulation under the nominal design condition is 85.77%, with a relative deviation of 0.55%, as compared with that from the one-dimensional optimization design. Furthermore, the static temperature and pressure from the turbine inlet to the outlet drop uniformly, and there is no obvious flow separation under the nominal design condition. The values of total-to-static efficiency are always higher than 75% at the 80–110% relative rotating speed and the expansion ratio of 1.75–4.48, which also demonstrates good performance under the off-design working conditions.

Evaluation of anticipated post-fire repair cost for resilient design of composite slab panels

The design limit states form the basis of current structural fire design approaches. These design practices overlook the post-fire resilience and repairability of the structure. Consequently, a minor fire might lead to an irreparable structure and a need of demolishing it. We propose a framework to evaluate during the design phase the anticipated repair cost for a structure in case of a fire event, in order to enable consideration of post-fire resilience in design decisions. We apply the framework to evaluate the repair cost for a composite slab panel comprising a concrete slab, two girder and two boundary beams at opposite edges, and two central beams at the center. Two fire designs for the composite slab panel satisfying the nominal fire design requirement are considered: a prescriptive design and a performance-based design which harnesses tensile membrane action and omits insulation on central beams. The repair costs are evaluated and compared for both designs for a range of natural fire exposures, demonstrating that the performance-based design achieves its target of stability during fire, but also results in higher anticipated post-fire damages. This concept of pre-evaluation of repair cost can further be implemented in life-cycle cost optimization procedures to allow an optimized structural design.

A Multi-Objective Factorial Design Methodology for Aerodynamic Off-Takes and Ducts

Fluid off-takes and complex delivery ducts are common in many engineering systems but designing them can be a challenging task. At the conceptual design phase many system parameters are open to consideration and preliminary design studies are necessary to instruct the conceptualisation process in an iterative development of design ideas. This paper presents a simple methodology to parametrically design, explore and optimise such systems at low cost. The method is then applied to an aerodynamic system including an off-take followed by a complex delivery duct. A selection of nine input variables is explored via a fractional factorial design approach that consists of three individual seven-level cubic factorial designs. Numerical predictions are characterised based on multiple aerodynamic objectives. A scaled representation of these objectives allows for a scalarisation technique to be employed in the form of a global criterion which indicates a set of trade-off geometries. This leads to the selection of a set of nominal designs and the determination of their robustness which will eventually instruct the next conceptual design iteration. The results are presented and discussed based on criterion space, design variable space and contours of several flow quantities on a selection of optimal geometries.

Modeling and Inversion of Airborne and Semi-Airborne Transient Electromagnetic Data with Inexact Transmitter and Receiver Geometries

Airborne and semi-airborne transient electromagnetic (TEM) surveys have high efficiency but may suffer from systematic errors due to the inexact shape, position, and orientation of the transmitter and receiver, which can deviate from the nominal design because of complex terrain, platform instability, or external forces. Without considering actual survey geometry, modeling and inversion can bias the interpretation of results. We develop a universal approach to layered earth capable of modeling arbitrarily complex transmitter and receiver geometry used in airborne and semi-airborne surveys. Our algorithm decomposes an airborne loop or grounded wire source to a set of x-, y-, or z-oriented electric dipoles. An arbitrarily oriented receiver coil is simulated by projecting three-component data to the actual direction of receiving. In airborne TEM, the transmitter loop and receiver coil are often bound together on a rigid frame and tilt during the flight. Our simulations and synthetic inversion show that such a tilt may reduce responses relative to the data obtained with the nominal geometry; an inversion without considering the tilt can underestimate near-surface conductivity. In semi-airborne TEM, the transmitter wire on the surface can be crooked, and the airborne receiver coil can also tilt. Our modeling shows that the simulated data can change significantly if the actual transmitter and receiver geometry does not exactly follow the nominal survey design; if not appropriately accounted for, such an error may distort the recovered conductivity model. Finally, the benefit of our algorithm is demonstrated by an airborne TEM field data inversion of groundwater problems with the tilt angle of the transmitter–receiver frame accurately modeled. Our work provides a tool for improving the resolution of airborne and semi-airborne TEM in near-surface conductivity characterization.

Bow-tie patch antenna for 5G

The goal of this work was to design, simulate, build, and test bow-tie antenna for 5G networks. In this paper, it will be shown how the radiation pattern and input match are improving by changing angles on some points of the antenna. The first angle is from the central point of the bow-tie antenna (mark A) and another angle is from the side points of the bow-tie antenna (mark B). Bandwidth improvement is shown in the simulation between 4 GHz and 6GHz. S11, E?, E? for the nominal design are -27.31 dB, 7.39 dB, -3.30 dB respectively. After simulations, the nominal antenna is fabricated and tested with reference antenna A-info LB8180. Simulation results, testing results with fabricated antenna, and angle change results will be shown in further text.

The DRAKE mission: finding the frequency of life in the Cosmos

ABSTRACT In the search for life in the Universe, exoplanets represent numerous natural experiments in planet formation, evolution, and the emergence of life. This raises the fascinating prospect of evaluating cosmic life on a statistical basis. One key statistic is the occurrence rate of life-bearing worlds, fL, the ‘frequency of life’ term in the famous Drake Equation. Measuring fL would give profound insight into how common life is and may help us to constrain origin-of-life theories. I propose fL as the goal for the DRAKE mission (Dedicated Research for Advancing Knowledge of Exobiology): a transit spectroscopy survey of M-dwarf habitable zone terrestrial planets. I investigate how the uncertainty on the observed value of fL scales with sample size. I determine that sampling error dominates over observational error and that the uncertainty is a function of the observed fL value. I show that even small sample sizes can provide significant constraints on fL, boding well for the transit spectroscopy approach. I perform a feasibility study of the DRAKE mission using a nominal instrument design and mission plan. Due to low observing efficiencies, DRAKE may need to be incorporated into a wider-ranging deep-space or lunar observatory. A 50-planet survey could constrain fL to ≤ 0.06 (at 95 per cent confidence) if the sample fL = 0, or 0.03–0.2 if the sample fL = 0.1. This can be achieved (on average) in 10 yr using a 17-m telescope with an unrestricted field-of-regard. DRAKE is a viable approach to attempting the first experimental measurement of fL.

Methodology for Shape Optimization of Magnetic Designs: Magnetic Spring Characteristic Tailored to Application Needs

Topology and shape optimization are still rarely applied to problems in electromagnetic design due to the computational complexity and limited commercial tooling, even though components such as electrical motors, magnetic springs or magnetic bearings could benefit from it, either to improve performance (reducing torque ripple and losses through shaping harmonic content in back electromotive force) or reduce the use of rare-earth materials. Magnetic springs are a fatigue free alternative to mechanical springs, where shape optimization can be exploited to a great degree—allowing for advanced non-linear stiffness characteristic shaping. We present the optimization methodology relying on a combination of several approaches for characteristic shaping of magnetic springs through either a modular design approach based on: (i) Fourier order decomposition; (ii) breaking conventional design symmetry; or (iii) free shaping of magnets through deviation from a nominal design using problem formulations such as spline and polynomials for material boundary definitions. Each of the parametrizations is formulated into a multi-objective optimization problem with both performance and material cost, and solved using gradient free optimization techniques (direct search, genetic algorithm). The methodology is employed on several benchmark problems—both academic and application inspired magnetic spring torque characteristic requirements. The resulting designs fit well with the requirements, with a relatively low computational cost. As such, the methodology presented is a promising candidate for other design problems in 2D shape optimization in electrical motor research and development.

3D FEA based surrogate modeling in fatigue crack growth life assessment

Runtime efficient models designed for damage tolerant life assessment are desired in Structural Health Management and Digital Twin development. While FEM is commonly used in the industry to assess health of a nominal structure design while in service, in probabilistic assessments, reduced order models are preferred due to lower runtime compared to the deterministic models but at the cost of solution accuracy. Readily available machine learning algorithms coupled with deterministic 3D simulations for modeling fatigue crack growth provide a feasible path to reach a better runtime-accuracy compromise. In this study, a fatigue crack growth testing procedure along with measurement data are used for validation purposes and for laying out details of the modeling process. Accuracy and solution runtime of the 3D FEA based surrogate models are assessed to demonstrate the efficiency of the method.

Effect of different supplementary cementitious materials on compressive strength of concrete with varying size of aggregates

In this rapid urbanization age, cement concrete is one of the most popular and demanding building materials. One of the components of concrete is roughly 12–15% cement. Overall, yearly cement manufacturing contributes around 7% of the world's CO2 emissions. As a result, the concrete industry is a global warming contributor. The goal of this research is to discover a method for mitigating the environmental risks that its production causes. Materials such as Fly Ash (FA), Rice Husk Ash (RHA), Silica Fume (SF), and Ground Granulated Blast Furnace Slag (GGBFS) are examples of supplementary cementitious materials (SCMs). If utilized as a substitute for cement in concrete, these components have the advantage of enhancing the strength of the concrete over time. This study shows the comparative effect of three SCMs i.e. FA, RHA and SF on compressive strength of concrete proportionated by Nominal Mix (NM) and Design Mix (DM) techniques both. In addition to that different ranges of aggregates 20 mm−12.5 mm, 9.55 mm−4.75 mm were also used to improve the packing density of concrete. During A total of sixty-six 15cmx15cmx15cm cubes were created for the experimental inquiry to measure the strength of cubes for varied curing durations of 14, 28, and 56 days. FA and RHA were utilized individually for partial cement replacement with proportions of 15%, 20%, 25 percent%, 30%, and SF with 10%, 15%, 20%, and the compressive strengths of 14 days, 28 days, and 56 days were computed using the compressive testing machine.

Thermally Constrained Conceptual Deep Geological Repository Design under Spacing and Placing Uncertainties

The temperature evolution within a deep geological repository (DGR) is a key design consideration for the safe and permanent storage of the high-level radioactive waste contained inside used nuclear fuel containers (UFCs). Due to the material limitations of engineered components with respect to high temperature tolerance, the Nuclear Waste Management Organization of Canada requires the maximum temperature within a future Canadian DGR to be less than 100 °C. Densely placing UFCs within a DGR is economically ideal, but greater UFC placement density will increase the maximum temperature reached in the repository. This paper was aimed to optimize (i) the separation between UFCs, (ii) the distance between container placement rooms, and (iii) the locations of the age-dependent UFCs in the placement rooms for a conceptual DGR constructed in crystalline rock. Surrogate-based optimization reduced the amount of computationally expensive evaluations of a COMSOL Multiphysics model used to study the temperature evolution within the conceptual DGR and determined optimal repository design points. Via yield optimization, nominal design points that considered uncertainties in the design process were observed. As more information becomes available during the design process for the Canadian DGR, the methods employed in this paper can be revisited to aid in selecting a UFC placement plan and to mitigate risks that may cause repository failure.

Evaluation of the Thermal Comfort and Energy Demand in a Building with Rammed Earth Walls in Spain: Influence of the Use of In Situ Measured Thermal Conductivity and Estimated Values

This paper describes the influence of thermal parameters—conductivity, transmittance, and thermal mass—in the estimation of comfort and energy demand of a building with rammed earth walls, and consequently, the compliance with standards. It is known that nominal design data does not match in situ measured values, especially in traditionally constructed buildings. We have therefore monitored a room in a building with rammed earth walls, designed a computerised model, and compared four different alternatives where we have changed the value for the thermal conductivity (in situ vs. estimated) and the consideration of thermal mass. When we then analyse the compliance with the Spanish energy saving code, using measured values would result in lower differences with the standards’ limits and even comply with the global thermal transmittance (K-value) requirement. This would mean a more realistic approach to the restoration of traditional buildings leading to the use of thinner and more suitable insulation and retrofitting systems, encouraging the use of rammed earth in new buildings, and therefore reducing the carbon footprint due to materials used in construction. Results show that the building model that uses in situ values and considers thermal mass (S1) is closer to reality when assessing thermal comfort. Finally, using nominal data would result in requiring 43% more energy in the selected winter period and 102% more energy in the selected summer period to keep the same comfort conditions as in the alternative where measured values are used.

DUNE Physics Program and Status

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino experiment with a 70-kt liquid argon detector at the Sanford Underground Research Facility (SURF) 1300 km from Fermilab. This programme includes studies of neutrino oscillations with a high-intensity muon-neutrino beam from Fermilab; as well as, proton decay and supernova neutrino burst searches. DUNE will resolve the neutrino mass hierarchy to a precision of 5σ, for all δCP values, after 2 years of running with the nominal detector design and beam configuration. It has the potential to observe charge-parity violation in the neutrino sector to a precision of 3σ (5σ) after an exposure of 5 (10) years, for 50% of all δCP values. The status and schedule of the project is also presented.

A part-load analysis and control strategies for the Graz Cycle

Carbon capture and storage (CCS) plays a uniquely important role in the future clean and dispatchable power generation portfolio to achieve the ambitious goals set at COP21. The Graz Cycle, a zero emission oxy-combustion power plant, is one of the most promising representatives of CCS power generation plants. The present work introduces different control strategies for the Graz Cycle and the corresponding part-load performances. The process simulation is composed of a design-point (full-load) and off-design (part-load) of the cycle. In order to do this, the process simulation tool IPSEpro was used. Individual cycle components were modelled for both investigations, full load and part load, and control strategies were developed in order to achieve optimum performances and operating efficiencies by means of the assumptions given. This work distinguishes from previous studies by the development of different control strategies and comparison of corresponding part-load performances. In the simulation, the Graz Cycle operating at nominal design conditions achieved a net plant efficiency of 53.1%. The part-load simulation generated results down to 40% load by applying three different control strategies. These control operation modes differ from each other in two basic parameters, boiler pressure and turbine inlet temperature. Optimum part-load performances were achieved by control strategy, where the pressure of the heat recovery steam generator is allowed to vary. However, other parameters, e.g. costs, did not appear to be favourable for this operation mode. The comparison with a readily available technology, such as a natural gas combined cycle, showed that the Graz Cycle is more efficient as loads are reduced below 50%.

Coherent-radiation-induced longitudinal single-pass beam breakup instability of a steady-state microbunch train in an undulator

It has been known that a high-brightness electron beam emits broadband synchrotron radiation when traversing a curved orbit. The radiation reaction at wavelengths comparable to the bunch length or to the wavelength of a phase space modulated beam may lead to collective instabilities. In this paper, we investigate a potential single-pass instability mechanism of coherent-radiation-induced longitudinal multibunch beam breakup (BBU) instability in the presence of a closely spaced microbunch train in an undulator, particularly when the microbunch spacing is close to the resonant wavelength of the undulator. This problem is formulated based on the macroparticle model together with the slippage constraint on the beam-wave interaction. The set of coupled differential equations for individual microbunches can be solved analytically for the first few microbunches with linearization of the coherent radiation wakefield, and numerically in general nonlinear cases for unequal spacing or nonuniform filling charges. The underlying mechanisms, including the slippage effect, the potential-well effect leading to extra focusing, dependence of microbunch spacing and filling patterns, are discussed. The analysis is then applied to the recently proposed steady-state microbunching (SSMB) mechanism with two examples serving for the high average coherent radiation power sources for extreme ultraviolet (EUV) and infrared wavelength regions. For the specific scenario considered in this paper, it is found that when the microbunch spacing is close to the fundamental resonant wavelength, the coherent radiation can provide extra longitudinal focusing for the individual microbunches, leading to more stable multibunch oscillations. For the preliminary nominal SSMB designs with the average beam current of 1 A, our studies show that the single-pass longitudinal BBU instability should not be a severe issue.

CRITICAL SHIFTING WINDOW IN SWITCHABLE ROCKER FINGER FOLLOWER


 
 
 
 A valvetrain including switchable rocker finger follower is capable of discrete switching between two modes (two cam profiles). The exact moment when switching occurs is called crossover point and this paper reviews the factors that cause the shift of the crossover point from its nominal design position. The range where crossover point can shift is called critical shifting window and its size and factors influencing it will be adressed.
 
 
 

Stator Blades Manufacturing Geometrical Variability in Axial Compressors and Impact on the Aeroelastic Excitation Forces

AbstractThe manufacturing geometrical variability is a source of uncertainty, which cannot be avoided in the realization of machinery components. Deviations of a part geometry from its nominal design are inevitably present due to the manufacturing process. In the case of the aeroelastic forced response problem within axial compressors, these uncertainties may affect the vibration characteristics. For this reason, the impact of geometrical uncertainties due to the manufacturing process onto the modal forcing of axial compressor blades is investigated in this study. The research focuses on the vibrational behavior of an axial compressor rotor blisk. In particular, the amplitude of the forces acting as a source of excitation on the vibrating blades is studied. The geometrical variability of the upstream stator is investigated as input uncertainty. The variability is modeled starting from a series of optical surface scans. A stochastic model is created to represent the measured manufacturing geometrical deviations from the nominal model. A data reduction methodology is proposed in order to represent the uncertainty with a minimal set of variables. The manufacturing geometrical variability model allows to represent the input uncertainty and probabilistically evaluate its impact on the aeroelastic problem. An uncertainty quantification is performed in order to evaluate the resulting variability on the modal forcing acting on the vibrating rotor blades. Of particular interest is the possible rise of low engine orders due to the mistuned flow field along the annulus. A reconstruction algorithm allows the representation of the variability during one rotor revolution. The uncertainty on low harmonics of the modal rotor forcing can be therefore identified and quantified.

BraggNet: Complex Photonic Integrated Circuit Reconstruction Using Deep Learning

We propose a deep learning model to reconstruct physical designs of complex coupled photonic systems, such as waveguide Bragg gratings, from their spectral responses for inverse design and fabrication diagnosis. Traditional reconstructing algorithms demand considerable computing resources at every query. Conversely, machine learning algorithms use most of the computing resources during the training process and provide effortless and orders-of-magnitude faster analysis in response to queries. This approach is demonstrated using silicon photonic grating-assisted, contra-directional couplers consisting of thousands of Bragg periods. The contra-directional couplers are modeled as coupled cavities, for which a transfer matrix model is used to generate a synthetic dataset comprising a strategic design parameter space. The free-form, architecture-independent model allows to include any geometries to the design parameter space. Upon proper training, the model achieves 1.4% mean absolute percentage error on device reconstruction and thus proves suitable for inverse design applications. To further show its potential for assessment of fabricated devices, another dataset is generated to emulate the fabrication conditions of a nominal design hindered by fabrication imperfections. The model is shown to reconstruct devices from experimental measurements with greater than 600-fold improvement in speed compared to the classical layer-peeling algorithm. This proves promising for data-driven processes required by Industry 4.0.