Development of design methodology for a small solar-powered unmanned aerial vehicle

Existing mathematical design models for small solar-powered electric unmanned aerial vehicles (UAVs) only focus on mass, performance, and aerodynamic analyses. Presently, UAV designs have low endurance. The current study aims to improve the shortcomings of existing UAV design models. Three new design aspects (i.e., electric propulsion, sensitivity, and trend analysis), three improved design properties (i.e., mass, aerodynamics, and mission profile), and a design feature (i.e., solar irradiance) are incorporated to enhance the existing small solar UAV design model. A design validation experiment established that the use of the proposed mathematical design model may at least improve power consumption-to-take-off mass ratio by 25% than that of previously designed UAVs. UAVs powered by solar (solar and battery) and nonsolar (battery-only) energy were also compared, showing that nonsolar UAVs can generally carry more payloads at a particular time and place than solar UAVs with sufficient endurance requirement. The investigation also identified that the payload results in the highest effect on the maximum take-off weight, followed by the battery, structure, and propulsion weight with the three new design aspects (i.e., electric propulsion, sensitivity, and trend analysis) for sizing consideration to optimize UAV designs

Predicting NOx emissions in diesel engines via sigmoid NARX models using a new experiment design for combustion identification

Diesel engines are still widely used in heavy-duty engine industry because of their high energy conversion efficiency. In recent decades, governmental institutions limit the maximum acceptable hazardous emissions of diesel engines by stringent international regulations, which enforces engine manufacturers to find a solution for reducing the emissions while keeping the power requirements. A reliable model of the diesel engine combustion process can be quite useful to search for the best engine operating conditions. In this study, nonlinear modeling of a heavy-duty diesel engine NOx emission formation is presented. As a new experiment design, air-path and fuel-path input channels were excited by chirp signals where the frequency profile of each channel is different in terms of the number and the direction of the sweeps. This method is proposed as an alternative to the steady-state experiment design based modeling approach to substantially reduce testing time and improve modeling accuracy in transient operating conditions. Sigmoid based nonlinear autoregressive with exogenous input (NARX) model is employed to predict NOx emissions with given input set under both steady-state and transient cycles. Models for different values of parameters are generated to analyze the sensitivity to parameter changes and a parameter selection method using an easy-to-interpret map is proposed to find the best modeling parameters. Experimental results show that the steady-state and the transient validation accuracies for the majority of the obtained models are higher than 80% and 70%, respectively

Simulation support for performance assessment of building components

The determination of performance metrics for novel building components requires that the tests are conducted in the outdoor environment. It is usually difficult to do this when the components are located in a full-scale building because of the difficulty in controlling the experiments. Test cells allow the components to be tested in realistic, but controlled, conditions. High-quality outdoor experiments and identification analysis methods can be used to determine key parameters that quantify performance. This is important for achieving standardised metrics that characterise the building component of interest, whether it is a passive solar component such as a ventilated window, or an active component such as a hybrid photovoltaic module. However, such testing and analysis does not determine how the building component will perform when placed in a real building in a particular location and climate. For this, it is necessary to model the whole building with and without the building component of interest. A procedure has been developed, and applied within several major European projects, that consists of calibrating a simulation model with high-quality data from the outdoor tests and then applying scaling and replication to one or more buildings and locations to determine performance in practice of building components. This paper sets out the methodology that has been developed and applied in these European projects. A case study is included demonstrating its application to the performance evaluation of hybrid photovoltaic modules

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces

Magnetorheological landing gear: 2. Validation using experimental data

Aircraft landing gears are subjected to a wide range of excitation conditions with conflicting damping requirements. A novel solution to this problem is to implement semi-active damping using magnetorheological (MR) fluids. In part 1 of this contribution, a methodology was developed that enables the geometry of a flow mode MR valve to be optimized within the constraints of an existing passive landing gear. The device was designed to be optimal in terms of its impact performance, which was demonstrated using numerical simulations of the complete landing gear system. To perform the simulations, assumptions were made regarding some of the parameters used in the MR shock strut model. In particular, the MR fluid's yield stress, viscosity, and bulk modulus properties were not known accurately. Therefore, the present contribution aims to validate these parameters experimentally, via the manufacture and testing of an MR shock strut. The gas exponent, which is used to model the shock strut's nonlinear stiffness, is also investigated. In general, it is shown that MR fluid property data at high shear rates are required in order to accurately predict performance prior to device manufacture. Furthermore, the study illustrates how fluid compressibility can have a significant influence on the device time constant, and hence on potential control strategies

Spark ignition internal combustion engine efficiency improvement - a variable compression ratio option

Pressure to reduce energy consumption is increasing. The problem of vehicle fuel consumption and emissions is approached by exploring various vehicle propulsion options, assessing their net eff�ectiveness on a energy conversion basis and on a usability (consumer appeal) basis. Life Cycle Assessment (LCA) of various options indicates that internal combustion engine powered vehicles compare favourably because of low production cost in spite of only achieving modest energy conversion efficiency in operation. Spark ignition (SI) homogeneous charge engines have dominated as passenger vehicle power plants, and are likely to maintain their prevalence for passenger vehicle propulsion into the future, but efficiency improvements are required and achievable. Throttling losses are a signifi�cant contributor to reduced efficiency at low load for SI engines which is the load range most employed in standard driving behaviour. An Induction Air Motor (IAM) was conceived, designed, simulated and prototyped to evaluate the potential to recover some of the work the engine does to reduce its intake air pressure for low load operation. The prototyped IAM produced work which potentially could contribute to the engine output while reducing the intake pressure resulting in improved efficiency. However, further eff�ort is required to reduce the friction in the IAM and optimise the work produced by the IAM. An alternative strategy for efficiency improvement involves high Compression Ratio (CR) in conjunction with a reduced compression stroke volume achieved by Late Valve Closing (LVC). Such an arrangement of the Atkinson cycle is shown by simulation to produce improved brake efficiency in SI engines. In this cofin�guration, the maximum power produced by the engine is considerably lower than the maximum power that is achieved by the same displacement for a full compression stroke. To achieve both the improved efficiency at low load using the Atkinson confi�guration and the power achievable from a full induction stroke, the engine requires Variable Compression Ratio (VCR). Assessment of VCR concepts from literature and patents identifi�ed that the complexity of continuously variable compression ratio designs prevented their development to production-ready con�figurations. A simulation of fuel consumption over a standard driving cycle showed that a two-position VCR arrangement produces the same bene�t as a continuously variable CR for physically achievable piston-rod-crank cofin�gurations. Experiments with supporting simulations were performed for a previously patented two-position VCR device, an eccentric link in the big-end of the connecting rod. This work concludes that the eccentric link is not a viable VCR mechanism. An alternative VCR device involving a hydraulic connecting rod was prompted by further experiments and simulations which identifi�ed the behaviour of oil when compressed at high rates in a hydraulic cylinder impacted by a falling mass. The oil impact work suggested that oil chambers of cross-sectional area that could be arranged in a conventional connecting rod could readily support the loads experienced by the rod in a conventionally con�figured engine, so the design and prototyping of a hydraulic connecting rod proceeded. Experiments and simulation confi�rmed that a relatively easily manufactured hydraulic connection rod can be successfully operated in an engine, achieving controllable two-position VCR. Further development of the hydraulic connecting rod control device and improved production techniques are recommended for this new two-position hydraulic VCR device

Post-test simulation of a PLOFA transient test in the CIRCE-HERO facility

CIRCE is a lead–bismuth eutectic alloy (LBE) pool facility aimed to simulate the primary system of a heavy liquid metal (HLM) cooled pool-type fast reactor. The experimental facility was implemented with a new test section, called HERO (Heavy liquid mEtal pRessurized water cOoled tubes), which consists of a steam generator composed of seven double-wall bayonet tubes (DWBT) with an active length of six meters. The experimental campaign aims to investigate HERO behavior, which is representative of the tubes that will compose ALFRED SG. In the framework of the Horizon 2020 SESAME project, a transient test was selected for the realization of a validation benchmark. The test consists of a protected loss of flow accident (PLOFA) simulating the shutdown of primary pumps, the reactor scram and the activation of the DHR system. A RELAP5-3D© nodalization scheme was developed in the pre-test phase at DIAEE of “Sapienza” University of Rome, providing useful information to the experimentalists. The model consisted to a mono-dimensional scheme of the primary flow path and the SG secondary side, and a multi-dimensional component simulating the large LBE pool. The analysis of experimental data, provided by ENEA, has suggested to improve the thermal–hydraulic model with a more detailed nodalization scheme of the secondary loop, looking to reproduce the asymmetries observed on the DWBTs operation. The paper summarizes the post-test activity performed in the frame of the H2020 SESAME project as a contribution of the benchmark activity, highlighting a global agreement between simulations and experiment for all the primary circuit physical quantities monitored. Then, the attention is focused on the secondary system operation, where uncertainties related to the boundary conditions affect the computational results

Series of experiments for empirical validation of solar gain modelling in building energy simulation codes - experimental setup, test cell characterization, specifications and uncertainty analysis

Empirical validation of building energy simulation codes is an important component in understanding the capacity and limitations of the software. Within the framework of Task 34/Annex 43 of the International Energy Agency (IEA), a series of experiments was performed in an outdoor test cell. The objective of these experiments was to provide a high-quality data set for code developers and modelers to validate their solar gain models for windows with and without shading devices. A description of the necessary specifications for modeling these experiments is provided in this paper, which includes information about the test site location, experimental setup, geometrical and thermophysical cell properties including estimated uncertainties. Computed overall thermal cell properties were confirmed by conducting a steady-state experiment without solar gains. A transient experiment, also without solar gains, and corresponding simulations from four different building energy simulation codes showed that the provided specifications result in accurate thermal cell modeling. A good foundation for the following experiments with solar gains was therefore accomplished