Optimization of the Capacities of Private Generators Installed in a Hospital Building Under the Constraint of Demand Sufficiency During Power Outages

It is essential to secure energy sources by installing a private power generator for business continuity in a power outage. The authors have developed an optimization tool to estimate the optimal amount of distributed power supply equipment using economic efficiency and resilience as two evaluation indicators. However, it is questionable whether the private generator in a hospital building can generate sufficient electricity to meet demands in case of a power failure, because demand has short cycle fluctuations on the order of seconds, and the private generator must respond to these fluctuations from time to time in the case of stand-alone operation. The optimization tools we have developed in the past have not considered the balance between power output and load demand (demand sufficiency). Therefore, this paper proposes a new optimization method that considers balancing power supply and demand in private generators’ independent operation during power outages. We narrowed the optimization constraints as demand sufficiency conditions: standard AC frequency range between 49 and 51 Hz. More practical optimal solutions are obtained by applying the new constraints to the multi-optimization. We also compare the case study results by applying these constraints to the results of previous case studies.

Stabilization of an Unconventional Large Airship when Hovering

In this paper, we present the stabilization of an unconventional unmanned airship above a loading and unloading area. The study concerns a quad-rotor flying wing airship. This airship is devoted to freight transport. However, during the loading and unloading phases, the airship is very sensitive to squalls. In this context, we present in this paper the dynamic model of the airship, and we propose a strategy for controlling it under the effects of a gust of wind. A feedforward/feedback control law is proposed to stabilize the airship when hovering. As part of the control allocation, the non-linear equations between the control vectors and the response of the airship actuators are highlighted and solved analytically through energy optimization constraints. A comparison with classical numerical algorithms was performed and demonstrated the power and interest of our analytic algorithm.

Optimization and Characteristics Analysis of High Torque Density 12/8 Switched Reluctance Motor Using Metaheuristic Gray Wolf Optimization Algorithm

In this paper, the optimization and characteristics analysis of a three-phase 12/8 switched reluctance motor (SRM) based on a Grey Wolf Optimizer (GWO) for electric vehicles (EVs) application is presented. This research aims to enhance the output torque density of the proposed SRM. Finite element method (FEM) was used to analyze the characteristics and optimization process of the proposed motor. The proposed metaheuristic GWO combines numerous objective functions and design constraints with different weight factors. Maximum flux density, current density, and motor volume are selected as the optimization constraints, which play a significant role in the optimization process. GWO performs optimization for each iteration and sends it to FEM software to analyze the performance before starting another iteration until the optimized value is found. Simulations are employed to understand the characteristics of the proposed motor. Finally, the optimized prototype motor is manufactured and performance is verified by experiment. It is shown that the torque can be increased by 120% for the same outer volume, by using the proposed method.

Linear Array Synthesis for Wireless Power Transmission Based on Brain Storm Optimization Algorithm

Based on the brain storm optimization algorithm, this paper proposed a new method to optimize the beam collection efficiency of the linear antenna array. In the process of optimization, constraints such as aperture size and minimum antenna spacing are considered. In this paper, the optimization with different antenna apertures, different antenna angles, and different array numbers are studied. A series of representative data and simulation results are given and the superiority of the brainstorming algorithm is demonstrated by comparing with the genetic algorithm.

Synergy between topology optimization and additive manufacturing in the automotive field

This article purposes on developing and on re-interpreting the numerical results of a topology optimization for a structural component built via additive manufacturing. A critical appraisal of the optimization results is presented by modeling the feasible component with a holistic approach that merges structural and manufacturing requirements. The procedure is expected to provide a design guideline for similar applications of practical relevance, toward an increase of the right-first-time parts that is required to bring additive manufacturing to its full competitiveness. Topology optimization of a steering upright for a Formula SAE racing car was performed by targeting weight minimization while complying with severe structural constraints, like global and local stiffness performance. Cornering, bumping and braking vehicle conditions were considered. The optimization constraints were evaluated via finite element analysis on a reference component, where the loading conditions were retrieved from telemetry data. The reference part was manufactured by computer numerical control machining from a solid aluminum block. Spurred by the interpretation of the topology optimization predictions, a new upright geometry was designed and validated by calculating its stress field and the possible occurrence of Euler buckling. The new upright was 9% lighter than the reference component. The new geometry was analyzed according to Design for Additive Manufacturing principles to choose the orientation on the build platform and the supports’ location and geometry. The part was successfully manufactured and proved consistent with the application.

TunnelCAM- A HDR Spherical Camera Array for Structural Integrity Assessments of Dam Interiors

The United States of America has an estimate of 84,000 dams of which approximately 15,500 are rated as high-risk as of 2016. Recurrent geological and structural health changes require dam assets to be subject to continuous structural monitoring, assessment and restoration. The objective of the developed system is targeted at evaluating the feasibility for standardization in remote, digital inspections of the outflow works of such assets to replace human visual inspections. This work proposes both a mobile inspection platform and an image processing pipeline to reconstruct 3D models of the outflow tunnel and gates of dams for structural defect identification. We begin by presenting the imaging system with consideration to lighting conditions and acquisition strategies. We then propose and formulate global optimization constraints that optimize system poses and geometric estimates of the environment. Following that, we present a RANSAC frame-work that fits geometric cylinder primitives for texture projection and geometric deviation, as well as an interactive annotation frame-work for 3D anomaly marking. Results of the system and processing are demonstrated at the Blue Mountain Dam, Arkansas and the F.E. Walter Dam, Pennsylvania.

Orthogonally coupled geometrical constraints in optics design

Modern optical multi-camera systems require integrating many camera modules in a small volume. A new space-saving concept for such imaging systems is presented, based on intersecting optical paths that utilize one or more common elements for the respective optical paths. The principles for the optimization for such systems is examined, providing the theory for geometric optimization constraints. These principles can become useful in designing e. g. spatially challenging 360-degree imaging systems for surveillance and consumer applications.