LGR-MPC: A user-friendly software based on Legendre-Gauss-Radau pseudo spectral method for solving Model Predictive Control problems

Active components, such as actuators, constitute a fundamental aspect of engineering systems, affording the freedom to shape system behavior as desired. However, this capability necessitates energy consumption, primarily in the form of electricity. Thus, a trade-off emerges between energy usage and desired outcomes. While open-loop optimal control methods strive for efficiency, practical implementation is hampered by disturbances and model discrepancies, underscoring the need for closed-loop controllers. The Proportional- Integral-Derivative (PID) controller is widely favored in industry due to its simplicity, despite sub-optimal responses in many cases. To bridge this gap, Model Predictive Control (MPC) offers a solution, yet its complexity limits its broad applicability. This paper introduces user-friendly Python-based MPC software, enabling easy access to MPC. The effectiveness of this software is demonstrated through multiple examples, including those with a known analytical solution.Comment: 19 pages, 16 figure

Nested Control Co-design of a Spar Buoy Horizontal-axis Floating Offshore Wind Turbine

Floating offshore wind turbine (FOWT) systems involve several coupled physical analysis disciplines, including aeroelasticity, multi-body structural dynamics, hydrodynamics, and controls. Conventionally, physical structure (plant) and control design decisions are treated as two separate problems, and generally, control design is performed after the plant design is complete. However, this sequential design approach cannot fully capitalize upon the synergy between plant and control design decisions. These conventional design practices produce suboptimal designs, especially in cases with strong coupling between plant and control design decisions. Control co-design (CCD) is a holistic design approach that accounts fully for plant-control design coupling by optimizing these decisions simultaneously. CCD is especially advantageous for system design problems with complex interactions between physics disciplines, which is the case for FOWT systems. This paper presents and demonstrates a nested CCD approach using open-loop optimal control (OLOC) for a simplified reduced-order model that simulates FOWT dynamic behavior. This simplified model is helpful for optimization studies due to its computational efficiency, but is still sufficiently rich enough to capture important multidisciplinary physics couplings and plant-control design coupling associated with a horizontal-axis FOWT system with a spar buoy floating platform. The CCD result shows an improvement in the objective function, annual energy production (AEP), compared to the baseline design by more than eleven percent. Optimization studies at this fidelity level can provide system design engineers with insights into design directions that leverage design coupling to improve performance. These studies also provide a template for future more detailed turbine CCD optimization studies that utilize higher fidelity models and design representations.Comment: 21 pages, 15 figures, 5 table

Internal Controls and Problems in Governmental Segment: Evidence from Iran

ABSTRACT In order to gain assurance of achieving the anticipating aims, successful accomplishment of activities in all areas, preventing any embezzlement, fraud, or misuse of resources and assets, and also fulfill the responsibilities of accountability for activities carried out, managers of state and private sectors design and implement the internal control systems. Regarding to the high volume use of the public resources in state sectors and the government's responsibilities in utilizing and conservation of such resources and its accountability, designing and implementation of internal control systems in state sector proves significant. Current paper is one applied kind researches, and has been carried out as a case study in state organizations of Zanjan province. The purpose of the research is not to apply the limitation theory in state organizations, but to discuss topics related to that and get acquaintance with significance of identifying the limitation and barriers of a system, and implements the limitation theory though in the system as the following step. Methodology, from the point of nature and content, is of descriptive and conductive type. Findings suggest that effective practical training of the financial staff, internal control regularities, and expert labor force prove as the trial conditions to accomplish the internal control effectively

Extracting Design Knowledge from Optimization Data: Enhancing Engineering Design in Fluid Based Thermal Management Systems

As mechanical systems become more complex and technological advances accelerate, the traditional reliance on heritage designs for engineering endeavors is being diminished in its effectiveness. Considering the dynamic nature of the design industry where new challenges are continually emerging, alternative sources of knowledge need to be sought to guide future design efforts. One promising avenue lies in the analysis of design optimization data, which has the potential to offer valuable insights and overcome the limitations of heritage designs. This paper presents a step toward extracting knowledge from optimization data in multi-split fluid-based thermal management systems using different classification machine learning methods, so that designers can use it to guide decisions in future design efforts. This approach offers several advantages over traditional design heritage methods, including applicability in cases where there is no design heritage and the ability to derive optimal designs. We showcase our framework through four case studies with varying levels of complexity. These studies demonstrate its effectiveness in enhancing the design of complex thermal management systems. Our results show that the knowledge extracted from the configuration design optimization data provides a good basis for more general design of complex thermal management systems. It is shown that the objective value of the estimated optimal configuration closely approximates the true optimal configuration with less than 1 percent error, achieved using basic features based on the system heat loads without involving the corresponding optimal open loop control (OLOC) features. This eliminates the need to solve the OLOC problem, leading to reduced computation costs.Comment: 13 pages, 20 figure

Multi-split configuration design for fluid-based thermal management systems

High power density systems require efficient cooling to maintain their thermal performance. Despite this, as systems get larger and more complex, human practice and insight may not suffice to determine the desired thermal management system designs. To this end, a framework for automatic architecture exploration is presented in this article for a class of single-phase, multi-split cooling systems. For this class of systems, heat generation devices are clustered based on their spatial information, and flow-split are added only when required and at the location of heat devices. To generate different architectures, candidate architectures are represented as graphs. From these graphs, dynamic physics models are created automatically using a graph-based thermal modeling framework. Then, an optimal fluid flow distribution problem is solved by addressing temperature constraints in the presence of exogenous heat loads to achieve optimal performance. The focus in this work is on the design of general multi-split heat management systems. The architectures discussed here can be used for various applications in the domain of configuration design. The multi-split algorithm can produce configurations where splitting can occur at any of the vertices. The results presented include 3 categories of cases and are discussed in detail.Comment: 11 pages, 18 figure

Advancing Fluid-Based Thermal Management Systems Design: Leveraging Graph Neural Networks for Graph Regression and Efficient Enumeration Reduction

In this research, we developed a graph-based framework to represent various aspects of optimal thermal management system design, with the aim of rapidly and efficiently identifying optimal design candidates. Initially, the graph-based framework is utilized to generate diverse thermal management system architectures. The dynamics of these system architectures are modeled under various loading conditions, and an open-loop optimal controller is employed to determine each system's optimal performance. These modeled cases constitute the dataset, with the corresponding optimal performance values serving as the labels for the data. In the subsequent step, a Graph Neural Network (GNN) model is trained on 30% of the labeled data to predict the systems' performance, effectively addressing a regression problem. Utilizing this trained model, we estimate the performance values for the remaining 70% of the data, which serves as the test set. In the third step, the predicted performance values are employed to rank the test data, facilitating prioritized evaluation of the design scenarios. Specifically, a small subset of the test data with the highest estimated ranks undergoes evaluation via the open-loop optimal control solver. This targeted approach concentrates on evaluating higher-ranked designs identified by the GNN, replacing the exhaustive search (enumeration-based) of all design cases. The results demonstrate a significant average reduction of over 92% in the number of system dynamic modeling and optimal control analyses required to identify optimal design scenarios.Comment: 13 pages, 17 figure

Histological Changes of the Ovary in Pregnant Mice Vaginally Exposed to Toxoplasma gondii

Background:Congenital toxoplasmosis is one cause of abortion. Infection can disrupt ovarian cycles and because toxoplasmosis is an infectious disease may have a similar effect on the ovaries. The purpose of this study was to investigate the pathological changes in the ovaries due to toxoplasmosis.  Methods:Tachyzoites of Toxoplasma gondii were harvested from peritoneal fluid of mice, experimentally infected. Two females and one male mouse were housed per cage for mating in the overnight. The pregnant mice were divided into experi-mental and control groups. Experimental group were infected by parasite but the control group received the normal saline. The experimental and control mice were euthanized. Ovaries and uterine horns of animals were removed and prepared for light microscopy. Results:Ovaries of infected pregnant mice presented gross morphological differ-ences compared to the control groups. In ovaries of experimental groups, changes of corpus luteum were observed. The comparison of experimental and control groups revealed that the number of primary follicles, secondary follicle, atretic pri-mary follicles and atretic secondary follicles had significant differences (P≤0.001). Conclusion:Toxoplasma gondii alters ovarian follicular growth and development in mice. In addition, it alters number of different phases of follicles and corpus lu-teum in ovaries of mice

Morphometric analysis of hypoglossal canal of the occipital bone in Iranian dry skulls

Background: The hypoglossal canal (HC) is in basal part of cranium that transmits the nerve that supplies the motor innervations to the muscles of tongue. Study on morphometry of (HC) and its variations has been a considerable interest field to neurosurgeons and research workers especially because of their racial and regional. Material and Methods: In this retrospective study, 26 adult dry human crania of no sex known were studied for (HC) and its variants. Thirty five skulls were observed for any damage of post cranial fossa and those in good condition (26 skulls)were selected. Sliding Vernier caliper was used for morphometric analysis. Results: There were significant difference between distances of: a-(HC) till anterior tip of condyles (right and left), b-(HC) till posterior tip of condyles (right and left), c-(HC)till lower border of occipital condyles (right and left), d-(HC) till external border of foramen jugular (right and left), e-(HC) till opisthion(right and left), f-(HC) till carotid canal (right and left), g-(HC) till jugular tubercle (right and left). There wasn′t significant difference in other parameters. Conclusion: Detailed morphometric analysis of (HC) will help in planning of surgical intervention of skull base in safer and easier ways

Asymmetric Effects of Oil Income Growth on Inflation in Iran: VECM Approach

Because of much dependence to oil revenues, Oil price fluctuations have much affect on Iranian economy. Since government possess a great deal of oil revenues and those financial government expenditure, then identifying manner and stringency of affecting shocks arise from oil revenue growth on inflation is very important. Subject of this paper is “Asymmetric effects of oil revenue growth on inflation in Iranian economy applying VECM method”. Our results indicate that both positive and negative shocks arise from oil revenue growth are inflationary