Classical Design Techniques Research Articles

Application of artificial intelligence in turbomachinery aerodynamics: progresses and challenges

Turbomachinery plays a vital role in energy conversion systems, with aerodynamic issues being integral to its entire lifecycle, spanning the period of design, validation, and maintenance. Conventionally, the reliance on skilled aerodynamic engineers has been pivotal in the successful development of turbomachines. However, in the current era of burgeoning artificial intelligence (AI) technology, researchers are increasingly turning to AI to replace human expertise and decision-making in these aerodynamic issues and to solve previously intractable aerodynamic problems. This paper presents a systematic literature review of the latest advancements in applying AI to turbomachinery aerodynamics, encompassing the design, validation, and maintenance of compressors and turbines. It underscores how AI is revolutionizing the research paradigm of turbomachinery aerodynamics. AI’s powerful learning capability facilitates more precise and convenient aerodynamic analyses and inspires innovative aerodynamic design ideas that go beyond the capabilities of classical design techniques. Additionally, AI’s autonomous decision-making capability can be employed for aerodynamic optimization and active flow control of turbomachines, generating optimal aerodynamic solutions and complex control strategies that surpass human brains. As a main contribution, we provide a detailed exposition of the future intelligent turbomachinery research and development (R &D) system, along with highlighting potential challenges such as physics embedding, interactive 3D design optimization, and real-time prognoses. It is anticipated that harnessing AI’s full potential will lead to a comprehensive AI-based turbomachinery R &D system in the future.

Power-Efficient Design of Large-Aperture Magnets for High-Energy Physics

A novel and sustainability-oriented approach to the design of large-aperture iron-dominated magnets is proposed, focusing on its application to charged particle momentum detection in high-energy experimental physics. As compared to classical design techniques, a broader number of goals and constraints is taken into account, considering jointly the detection performance, the minimization of both the electrical power and magnet size, and the electromagnetic efficiency. A case study is considered for the detector magnet of a specific experiment, where the optimal design is pursued with semi-analytical tools, duly introducing the main quantities’ scaling laws in analytical form and successively validating the results with 3D numerical tools. A solution at higher energy efficiency is obtained, as compared to a more traditional design point of view. The proposed methodology can be fruitfully employed also in the design of magnets with a reduced ecological footprint in a number of other industrial and medical applications.

The Application of the Characteristics and Design Techniques of Jiangnan Classical Gardens in Suzhou Museum

Suzhou Museum is located in the garden zone of Suzhou. As a translation of classical garden design techniques in today's architecture, it has become the landmark cultural architecture of Suzhou city.Taking Suzhou Museum as an example, this paper explores the application of Jiangnan classical gardens in modern architectural design from two aspects of features and design techniques, so as to contribute to the discussion on the inheritance and development of classical garden culture.

Learning to Optimise a Swarm of UAVs

The use of Unmanned Aerial Vehicles (UAVs) has shown a drastic increase in interest in the past few years. Current applications mainly depend on single UAV operations, which face critical limitations such as mission range or resilience. Using several autonomous UAVs as a swarm is a promising approach to overcome these. However, designing an efficient swarm is a challenging task, since its global behaviour emerges solely from local decisions and interactions. These properties make classical multirobot design techniques not applicable, while evolutionary swarm robotics is typically limited to a single use case. This work, thus, proposes an automated swarming algorithm design approach, and more precisely, a generative hyper-heuristic relying on multi-objective reinforcement learning, that permits us to obtain not only efficient but also reusable swarming behaviours. Experimental results on a three-objective variant of the Coverage of a Connected UAV Swarm problem demonstrate that it not only permits one to generate swarming heuristics that outperform the state-of-the-art in terms of coverage by a swarm of UAVs but also provides high stability. Indeed, it is empirically demonstrated that the model trained on a certain class of instances generates heuristics and is capable of performing well on instances with a different size or swarm density.

Dynamical Link Budget in Satellite Communications at Ka-Band: Testing Radiometeorological Forecasts With Hayabusa2 Deep-Space Mission Support Data

The weather-forecast based Radio Meteorological Operation Planner (RMOP) model for the dynamical link-budget design in satellite communications at Ka-band is described and validated. For the first time, actual received Ka-band data from a deep-space satellite mission (Hayabusa2 mission from JAXA and supported by ESA) were available for operational tests. RMOP-predicted link-budget parameters were delivered in real-time before each scheduled satellite transmission period. After each transmission, received data measured by the ground stations were exploited for the RMOP validation. The data-volume actually received (transmitted and lost) by Hayabusa2 was compared with the one that would have been obtained if the transmission had been configured according to RMOP predictions. The results prove that RMOP model is capable of receiving more than 100% of extra data-volume with respect to the classical link-budget design techniques while keeping data losses under control. A specific approach usable in case of rainy events is described, too. These outstanding results will pave the way to an operative use of the weather-forecast based RMOP model for future satellite missions.

Controller considerations for attenuating noise in process variables in presence of uncertainties in plant parameters

This paper analyzes the effect of uncertainties on noise amplification in the internal model control (IMC) and classical control design technique. It is observed that IMC based on integral absolute error (IAE) design criteria (IMC-IAE) boosts noise in the process variables, system output as well as in control input for certain class of systems. Moreover, the resulting control system becomes highly sensitive at high frequency with uncertainty in plant parameters which further boosts noise in process variables. Integral square error (ISE) based IMC (IMC-ISE) is, however, free from the issues of sensitivity and noise amplification at high frequencies and not analyzed in this paper. This issue also exists in well known classical controllers such as PID controller, lead, lag, lead-lag compensators, etc. The solution to this problem is to choose the controller such that the open loop transfer function (OLTF) and hence the closed loop transfer function (CLTF) are strictly proper, and a formal proof to this effect is laid down in this paper. Further, simulation study is carried out to show the impact of noise and the effect of plant uncertainty in output and control input for IMC-IAE control system. The proposed theory is validated experimentally on a DC servo system by comparing noise power of the control input for IMC-IAE and PID controllers.

L₁-Adaptive Robust Control Design for a Pressurized Water-Type Nuclear Power Plant

This work proposes adaptive control-based design strategies to control a pressurized water reactor (PWR) nuclear power plant (NPP). An L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -adaptive-based state-feedback control technique is proposed using the linear quadratic Gaussian control and projection-based adaptation laws. The control scheme possesses good robustness capabilities in handling disturbances and uncertainties. A robust L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -adaptive control technique is also proposed by combining the L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -adaptive control with the loop transfer recovery (LTR) technology. The framework hence gives the strengthened robust set-point tracking performance given the matched and unmatched uncertainties and disturbances. The NPP model employed in this article is defined by five inputs, five outputs, and 38 state variables. A linear model for controller design is obtained by linearizing the nonlinear NPP model at operating conditions. Various simulations are carried out on subsystems of the NPP to verify the effectiveness of the proposed scheme. Numerical and statistical measures are computed for quantitative analysis of the controllers' performance. Several classical control design techniques are also implemented, and their performance is compared with the proposed adaptive control techniques.

Selection of Optimal Operating Conditions for Extraction of Myrtus Communis L. Essential Oil by the Steam Distillation Method.

Myrtus communis L. is one of the important aromatic and medicinal species from the Mediterranean area. It is used in various fields such as culinary, cosmetic, pharmaceutical, therapeutic, and industrial applications. Thus, a Box–Wilson experimental plan was used in this study to select the optimal operating conditions in order to obtain high volumes of essential oils. The factorial design method was applied to evaluate at an industrial scale the effect of major process variables on the essential oil extraction from Myrtus communis L. herbs by the steam distillation method. The input variables considered as significant operating conditions were: X1—boiler occupancy rate (boilers were filled to 50%, 75%, and 100%), X2—distillation duration (distillation was continued 60, 75, and 90 min), and X3—particle size (herbs were cut in sizes of 10, 20, and 30 mm via guillotine). The dependent variable selected, coded as Y, was the essential oil volume obtained (mL). The steps of the classical statistical experimental design technique were complemented with the Taguchi method to improve the extraction efficacy of essential oil from Myrtus communis L., and the optimum parameter conditions were selected: boiler occupancy rate 100%, distillation duration 75 min, and particle size 20 mm. Following the optimum parameters, the GC-MS assay revealed for the Myrtus communis L. essential oil two predominant components, α-pinene—33.14% and eucalyptol—55.09%.

Evaluación experimental del rendimiento de los controladores Fuzzy aplicados en un sistema fotovoltaico autónomo

En este artículo se pretende llevar a cabo una evaluación experimental de la utilización de técnicas de asignación de polos en el control Fuzzy aplicadas al flujo de CC en un sistema fotovoltaico autónomo, con el fin de garantizar una condición de estabilidad y un determinado rendimiento para la operación del sistema. Es presentado en la primera etapa del trabajo un modelo matemático que describe adecuadamente el comportamiento dinámico en cuestión fue linealizado el sistema en torno a un punto de operación haciendo uso de las series de Taylor, seguido por el análisis en un ambiente computacional del modelo linealizado del sistema fotovoltaico. Posteriormente, se evaluó de manera experimental el comportamiento dinámico en lazo abierto del sistema fotovoltaico autónomo, observando sus principales variables eléctricas (voltaje y corriente eléctrica). En la segunda etapa del trabajo, se investigó experimentalmente la aplicación de las técnicas de diseño de controladores PI clásico y controladores Fuzzy, con el objetivo de evaluar el comportamiento dinámico del sistema en lazo cerrado y garantizar la estabilidad de este, para pruebas en la variación del voltaje de referencia. Por fin, se presentaron los resultados de la evaluación experimental que demostró un mejor desempeño del controlador Fuzzy en comparación al controlador proyectado por la metodología clásica, cuando utilizada una planta fotovoltaica autónoma

OEDIPUS: An Experiment Design Framework for Sparsity-Constrained MRI.

This paper introduces a new estimation-theoretic framework for experiment design in the context of MR image reconstruction under sparsity constraints. The new framework is called OEDIPUS (Oracle-based Experiment Design for Imaging Parsimoniously Under Sparsity constraints) and is based on combining the constrained Cramér-Rao bound with classical experiment design techniques. Compared to popular random sampling approaches, OEDIPUS is fully deterministic and automatically tailors the sampling pattern to the specific imaging context of interest (i.e., accounting for coil geometry, anatomy, image contrast, etc.). OEDIPUS-based experiment designs are evaluated using retrospectively subsampled in vivo MRI data in several different contexts. The results demonstrate that OEDIPUS-based experiment designs have some desirable characteristics relative to conventional MRI sampling approaches.

An Efficient Cloud Market Mechanism for Computing Jobs With Soft Deadlines

This paper studies the cloud market for computing jobs with completion deadlines, and designs efficient online auctions for cloud resource provisioning. A cloud user bids for future cloud resources to execute its job. Each bid includes: 1) a utility, reflecting the amount that the user is willing to pay for executing its job and 2) a soft deadline, specifying the preferred finish time of the job, as well as a penalty function that characterizes the cost of violating the deadline. We target cloud job auctions that executes in an online fashion, runs in polynomial time, provides truthfulness guarantee, and achieves optimal social welfare for the cloud ecosystem. Towards these goals, we leverage the following classic and new auction design techniques. First, we adapt the posted pricing auction framework for eliciting truthful online bids. Second, we address the challenge posed by soft deadline constraints through a new technique of compact exponential-size LPs coupled with dual separation oracles. Third, we develop efficient social welfare approximation algorithms using the classic primal-dual framework based on both LP duals and Fenchel duals. Empirical studies driven by real-world traces verify the efficacy of our online auction design.

Concept for a new approach to project management in the activities of public servants

Natalia F. Altukhova - Associate Professor, Head of Department of Business Informatics, Financial University under the Government of the Russian FederationAddress: 38, Scherbakovskaya Street, Moscow, 105187, Russian Federation E-mail: nfaltuhova@fa.ruElena V. Vasileva - Professor, Department of Business Informatics. Financial University under the Government of the Russian FederationAddress: 38, Scherbakovskaya Street, Moscow, 105187, Russian Federation E-mail: evvasileva@fa.ruBoris B. Slavin - Scientific Advisor, Faculty of Applied Mathematics and Information Technology, Professor, Department of Business Informatics, Financial University under the Government of the Russian FederationAddress: 38, Scherbakovskaya Street, Moscow, 105187, Russian Federation E-mail: bbslavin@fa.ru This article presents the results of research into the possibility of adapting flexible methods of project management to the organization of activities of public servants of the Russian Federation and recommendations on combined approaches. The objectives of this research: to identify special aspects of project management in the public service and to evaluate the possibilities for adapting flexible methods of project management to the organization of activities of Russian public servants. The activities of the public service are becoming increasingly innovative and intelligent and, as a consequence, less predictable. These days the public authorities are not only customers in relation to third organizations, but they themselves act as the direct executors of projects in the elaboration of development programs and legislative initiatives in the framework of executing orders of the President, Government and the higher state authorities. In these circumstances, management principles of the PMBOK and similar standards, which are strictly formalized and require clear planning of processes, no longer work. When the problems are large-scale, technologies are known, and the resources are defined, classical design techniques work flawlessly. But when any innovative goals are set, there may be high risk of exceeding budget funds and time; therefore in this case it is necessary to consider the feasibility of applying Agile-like technologies. Possibilities for the combination of tough methods (in terms of responsibility and formalization) and flexible methods (in terms of goal-setting and continuity) of project management in the civil service were investigated using analysis of business processes and based on the results of a survey of the public servants participating in the implementation of certain tasks with respect to execution of public functions. It is noted that in contrast to the business-oriented organizations the government authorities are characterized by a significantly reduced motivation to informal leadership and undeveloped self-organization and self-management. This fact imposes restrictions on the processes of implementing approaches of flexible project management in the activities of public servants, but it does not mean it is impossible to formulate and use them. Based on the results of the study we carried out, we determined principles of flexible project management in the civil service, the knowledge of which can be useful both for the public servants and businesses working with government agencies.[1] This article was prepared based on the results of research carried with the support of government funds by the State Order of the University of Finance for the year of 2016 “Analysis of the best international practices of information support to realization of public functions. Development of proposals on improvement of information support to activities of civil public servants”, state registration number AAAA-A16-116070610054-7

Correct-by-Construction Adaptive Cruise Control: Two Approaches

Motivated by the challenge of developing control software provably meeting specifications for real-world problems, this paper applies formal methods to adaptive cruise control (ACC). Starting from a linear temporal logic specification for ACC, obtained by interpreting relevant ACC standards, we discuss in this paper two different control software synthesis methods. Each method produces a controller that is correct-by-construction, meaning that trajectories of the closed-loop systems provably meet the specification. Both methods rely on fixed-point computations of certain set-valued mappings. However, one of the methods performs these computations on the continuous state space whereas the other method operates on a finite-state abstraction. While controller synthesis is based on a low-dimensional model, each controller is tested on CarSim, an industry-standard vehicle simulator. Our results demonstrate several advantages over classical control design techniques. First, a formal approach to control design removes potential ambiguity in textual specifications by translating them into precise mathematical requirements. Second, because the resulting closed-loop system is known a priori to satisfy the specification, testing can then focus on the validity of the models used in control design and whether the specification captures the intended requirements. Finally, the set from where the specification (e.g., safety) can be enforced is explicitly computed and thus conditions for passing control to an emergency controller are clearly defined.

QFT Based Robust Positioning Control of the PMSM Using Automatic Loop Shaping with Teaching Learning Optimization

Automation of the robust control system synthesis for uncertain systems is of great practical interest. In this paper, the loop shaping step for synthesizing quantitative feedback theory (QFT) based controller for a two-phase permanent magnet stepper motor (PMSM) has been automated using teaching learning-based optimization (TLBO) algorithm. The QFT controller design problem has been posed as an optimization problem and TLBO algorithm has been used to minimize the proposed cost function. This facilitates designing low-order fixed-structure controller, eliminates the need of manual loop shaping step on the Nichols charts, and prevents the overdesign of the controller. A performance comparison of the designed controller has been made with the classical PID tuning method of Ziegler-Nichols and QFT controller tuned using other optimization algorithms. The simulation results show that the designed QFT controller using TLBO offers robust stability, disturbance rejection, and proper reference tracking over a range of PMSM’s parametric uncertainties as compared to the classical design techniques.

R-RoMulOC: A unified tool for randomized and robust multiobjective control

In this paper, we describe the salient features of a newly released toolbox for Matlab in dealing with systems with uncertainties. The toolbox combines classical robust multiobjective design techniques with the recently developed randomized approach, providing to the user a wide range of tools for performing deterministic and probabilistic analysis and design.

Design and control of a bio-inspired soft wearable robotic device for ankle–foot rehabilitation

We describe the design and control of a wearable robotic device powered by pneumatic artificial muscle actuators for use in ankle–foot rehabilitation. The design is inspired by the biological musculoskeletal system of the human foot and lower leg, mimicking the morphology and the functionality of the biological muscle–tendon–ligament structure. A key feature of the device is its soft structure that provides active assistance without restricting natural degrees of freedom at the ankle joint. Four pneumatic artificial muscles assist dorsiflexion and plantarflexion as well as inversion and eversion. The prototype is also equipped with various embedded sensors for gait pattern analysis. For the subject tested, the prototype is capable of generating an ankle range of motion of 27° (14° dorsiflexion and 13° plantarflexion). The controllability of the system is experimentally demonstrated using a linear time-invariant (LTI) controller. The controller is found using an identified LTI model of the system, resulting from the interaction of the soft orthotic device with a human leg, and model-based classical control design techniques. The suitability of the proposed control strategy is demonstrated with several angle-reference following experiments.

Design Technique and modification of Power line filter using passive lumped components

A unique design technique of power line filter is being proposed. It is based on the conventional technique of composite low pass filter. The equivalent circuit of the composite low pass filter is being presented in the two different modes by considering the modal propagation of noise. The consideration of composite LPF is taken into account in the design technique of power line filter. In order to accurately predict the insertion loss of the filter the effects of non-ideal behaviour of the passive lumped components are considered. It is based on the parasitic effect of the passive lumped elements. The filter is then characterized using S-parameters. The response of the filter's circuits is simulated using advanced design software (ADS). Keywords: Conducted emission, Composite filter, electromagnetic compatibility, lumped elements, and power line filter. I. Introduction Switching and modulation techniques are used for efficient use of electrical power. Widely used Switched mode power supplies (SMPS) for powering today's electronics loads is a most common example. Unfortunately, all the power control techniques deliberately distort sinusoidal wave form of power frequency and generate unwanted interfering signals. Obviously, they all are often cited as one of the main source of conducted emission (CE). Usually the power supplies which are using controlling techniques cannot comply with the strict electromagnetic compatibility (EMC) regulations. In order to meet the limit set for conducted EMI, power supplies require a filter at its input. Conducted EMI generated through particular equipment gets coupled into other equipments mostly through power line cables. CE can be controlled by using filters and increasing line impedance. Conducted EMI has two components: The common mode (CM) interference and differential mode (DM) interference. The coupling mechanisms of these interferences are different (4). The difference in the direction of propagation of these coupling currents along the phase and neutral line, leads to differential mode ( ) current and common mode ( ) current. Therefore design of EMI filters demand decoupling of these two modes (2). This paper attempts to describe a design technique for Power Line filter using classical design technique. 1.1 Characterization of common mode & differential mode currents

Optimally designing experiments under non-standard experimental situations

There are numerous situations in which experiments need to be optimally designed since classic experimental design techniques are no longer effective. The experimental design space may be constrained, or already-performed experiments may have to be included. The experiment may involve qualitative factors with more than two levels, mixture and process factors in the same design, or a specific set of design points. In addition, the situation may call for reducing the number of experimental runs or using a reduced regression model in fitting the data. Finally, the region where the model is to be fitted may not be the same as where the measurements are to be made, or the model errors may have a known correlation matrix. Unfortunately, researchers in the experimental design community have paid full attention to only a few popular optimal designs; however, there are a number of other optimal designs which may be useful under different experimental situations. The main objective of this paper is the collective documentation of a broad spectrum of optimal design families, application areas, and key mathematical properties.

Classical controller design techniques for fractional order case

This paper presents some classical controller design techniques for the fractional order case. New robust lag, lag-lead, PI controller design methods for control systems with a fractional order interval transfer function (FOITF) are proposed using classical design methods with the Bode envelopes of the FOITF. These controllers satisfy the robust performance specifications of the fractional order interval plant. In order to design a classical PID controller, an optimization technique based on fractional order reference model is used. PID controller parameters are obtained using the least squares optimization method. Different PID controller parameters that satisfy stability have been obtained for the same plant.

Electric transfer function model of switched reluctance motors and model‐based current control design

AbstractThis paper presents a current control design for switched reluctance motors (SRMs). The electric transfer characteristic of the motors is studied first. Their transfer function is shown to be expressible by a pure resistive component, which is not constant but varies depending on the motor current and speed. The current control design for SRMs follows the classical design technique used for DC machines, where the zeros of the PI controller cancel the poles of Ls+R. Because the transfer function of SRMs does not have any poles, an I controller is suitable for them. The integral gain should be adjusted in order to compensate the nonlinearity, that is, the variation in the equivalent resistor of the SRMs' transfer function. The values of the integral gain are tuned and tabulated for the motor speed and current. Simulation and experiment demonstrate that the current and speed of the SRMs present good responses without dependence on the motor speed and current. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 173(1): 51–59, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20987