This work investigates the impact of position and attitude perturbations on the beamforming performance of multi-satellite systems. The system under analysis is a formation of small satellites equipped with direct radiating arrays that synthesise a large virtual antenna aperture. The results show that performance is highly sensitive to the considered perturbations. However, by incorporating position and attitude information into the beamforming process, nominal performance can be effectively restored. These findings support the development of control-aware beamforming strategies that tightly integrate the attitude and orbit control system with signal processing to enable robust beamforming and autonomous coordination.
Niklas Braun, Markus Steimle, Martin Törngren
et al.
As simulation is increasingly used in scenario-based approaches to test Automated Driving Systems, the credibility of simulation results is a major concern. Arguably, credibility depends on the validity of the simulation setup and simulation models. When selecting appropriate simulation models, a trade-off must be made between validity, often connected to the model's fidelity, and cost of computation. However, due to the large number of test cases, expert-based methods to create sufficiently valid simulation setups seem infeasible. We propose using design contracts in order to semi-automatically compose simulation setups for given test cases from simulation models and to derive requirements for the simulation models, supporting separation of concerns between simulation model developers and users. Simulation model contracts represent their validity domains by capturing a validity guarantee and the associated operating conditions in an assumption. We then require the composition of the simulation model contracts to refine a test case contract. The latter contract captures the operating conditions of the test case in its assumption and validity requirements in its guarantee. Based on this idea, we present a framework that supports the compositional configuration of simulation setups based on the contracts and a method to derive runtime monitors for these simulation setups.
Intelligent reflecting surface (IRS) is a potential candidate for massive multiple-input multiple-output (MIMO) 2.0 technology due to its low cost, ease of deployment, energy efficiency and extended coverage. This chapter investigates the slot-by-slot IRS reflection pattern design and two-timescale reflection pattern design schemes, respectively. For the slot-by-slot reflection optimization, we propose exploiting an IRS to improve the propagation channel rank in mmWave massive MIMO systems without need to increase the transmit power budget. Then, we analyze the impact of the distributed IRS on the channel rank. To further reduce the heavy overhead of channel training, channel state information (CSI) estimation, and feedback in time-varying MIMO channels, we present a two-timescale reflection optimization scheme, where the IRS is configured relatively infrequently based on statistical CSI (S-CSI) and the active beamformers and power allocation are updated based on quickly outdated instantaneous CSI (I-CSI) per slot. The achievable average sum-rate (AASR) of the system is maximized without excessive overhead of cascaded channel estimation. A recursive sampling particle swarm optimization (PSO) algorithm is developed to optimize the large-timescale IRS reflection pattern efficiently with reduced samplings of channel samples.
In this work, the process of biogas production from palm oil factory effluent was simulated and then the produced biosynthetic gas was sweetened. For this purpose, the biogas production process from wastewater treatment was simulated using SuperPro Designer v9.0 software. Then, the resulting biogas entered the chemical absorption and reforming sections for sweetening and conversion to syngas, respectively, and these steps were simulated with Aspen HYSYS v11.0 software. The simulation results of the first stage showed that the effluent feed of this factory with a flow rate of 42000 kg/h and COD of 62000 mg/L leads to the production of 1786 kg/h biogas containing various compounds such as methane, carbon dioxide, hydrogen sulfide and water with the molar fraction of 0.446, 0.245, 0.178 and 0.040, respectively. In the chemical absorption section, MEA solvent 10 %wt. and solvent-to-gas molar ratio of 13.51 were used, which led to the efficient removal of CO2 and H2S up to 1 ppm and 99.99%, respectively. The examination of temperature changes in the absorption tower also showed that the temperature increases along the absorption tower. In the methane steam-reforming unit, two different strategies were used: 1) plug flow reactor (with fluid package of Peng-Robinson-Stryjek–Vera) and 2) conversion and equilibrium reactors (with fluid package of Peng-Robinson). The results showed that the purity of hydrogen in the biogas produced in the second strategy (conversion and equilibrium reactors) was higher than the first one (plug flow reactor), and on the other hand, the purity of CO2 was zero in the second strategy.
Technology, Water supply for domestic and industrial purposes
Niki Soleimani Amiri, Sina Ebrahimi, Mahdi Emadi
et al.
Leachate production and management is a challenging environmental issue in municipal landfills and depots in Iran. Leachate contains toxic materials, heavy metals, and organic and microbial pollutants on a significant scale. Its uncontrolled entrance into the surface, groundwater, and soils can also substantially inverse impacts on human health and natural habitats. In Mazandaran province, during the last decades, depots and landfilling of municipal and industrial waste have led to environmental degradation in its eco-sensitive natural zones and brought a series of health, social, and security challenges to the region. Due to the region's high precipitation rate and landfills with no cover, these places practically convert into an extensive resource for leachate production. To diminish the environmental impacts, a lot of work has been done in recent years to develop a sort of leakage gathering system and treatment plants in these landfills, based primarily on an overall estimation. In this study, a calculating computer model has been developed for leakage production based on regional climate conditions and the characteristics of municipal waste. This model is different from the HELP model, which is commonly used for sanitary landfills and is specifically developed for the waste depots of the Mazandaran province. In this model, hydrological methods, which are based on the water balance in the landfill sites, were used for the calculation. The developed model was uploaded as an online service for public use. By referring to the internet address provided, the developed model in the landfill part and the leachate section, the amount of produced leachate for the landfill site of Mazandaran province can be calculated. Also, the leachate volume of the Babol Anjilsi landfill has been calculated as a case study. As a result of this study, the lowest and highest amount of the production leachate for hot and dry months of the year (June and July) and for wet and rainy months (October) was about 63.39 and 260.07 cubic meters per day, respectively.
Technology, Water supply for domestic and industrial purposes
The present research, by problematizing the water crisis in Iran and Kurdistan province, has tried to analyze the situation of institutional and public water transfer disputes as a solution to this crisis. In this regard, the question of whether the transfer of water in the province has provided an opportunity for its development or if it has led to development bottlenecks, analyzing the debates and controversies of two institutional perspectives in the form of experts and managers of the regional water company of the province has been raised. Kurdistan and civil and environmental activists are concerned about the transfer of water from the west to the east of the province. Therefore, the sustainable development approach, which seeks the connection and interaction of the three spheres of society, economy and environment, has formed the theoretical basis of this research. The methodology is based on theoretical and experimental goals and position, while institutional ethnography is based on the experiences, knowledge, views of the interviewees [31 semi-structured interviews], and the review of statistics and documents related to the discussion of water, and its leading crisis has been water transfer in Kurdistan province. According to the analysis of 6 secondary categories, the results show that managers and experts consider climate change and natural obstacles to water exploitation as the basis of many conditions and obstacles to sustainable management of water resources, while activists focus on the weakness of sustainable management of water resources. They also emphasize, managers and institutional experts highlight the lack of integrated water management and the lack of funds as the basis of institutional weakness and the indifference of the academic elite and provincial representatives to the water issue, and the lack of bargaining power in allocating water to the province. They consider political issues and lack of public participation as the reason for this. And finally, it can be concluded that water transfer is not considered an opportunity but a bottleneck and challenge for the province's development.
Technology, Water supply for domestic and industrial purposes
Electric autonomous vehicles (EAVs) are getting attention in future autonomous mobility-on-demand (AMoD) systems due to their economic and societal benefits. However, EAVs' unique charging patterns (long charging time, high charging frequency, unpredictable charging behaviors, etc.) make it challenging to accurately predict the EAVs supply in E-AMoD systems. Furthermore, the mobility demand's prediction uncertainty makes it an urgent and challenging task to design an integrated vehicle balancing solution under supply and demand uncertainties. Despite the success of reinforcement learning-based E-AMoD balancing algorithms, state uncertainties under the EV supply or mobility demand remain unexplored. In this work, we design a multi-agent reinforcement learning (MARL)-based framework for EAVs balancing in E-AMoD systems, with adversarial agents to model both the EAVs supply and mobility demand uncertainties that may undermine the vehicle balancing solutions. We then propose a robust E-AMoD Balancing MARL (REBAMA) algorithm to train a robust EAVs balancing policy to balance both the supply-demand ratio and charging utilization rate across the whole city. Experiments show that our proposed robust method performs better compared with a non-robust MARL method that does not consider state uncertainties; it improves the reward, charging utilization fairness, and supply-demand fairness by 19.28%, 28.18%, and 3.97%, respectively. Compared with a robust optimization-based method, the proposed MARL algorithm can improve the reward, charging utilization fairness, and supply-demand fairness by 8.21%, 8.29%, and 9.42%, respectively.
Environmentally-powered computer systems operate on renewable energy harvested from their environment, such as solar or wind, and stored in batteries. While harvesting environmental energy has long been necessary for small-scale embedded systems without access to external power sources, it is also increasingly important in designing sustainable larger-scale systems for edge applications. For sustained operations, such systems must consider not only the electrical energy but also the thermal energy available in the environment in their design and operation. Unfortunately, prior work generally ignores the impact of thermal effects, and instead implicitly assumes ideal temperatures. To address the problem, we develop a thermodynamic model that captures the interplay of electrical and thermal energy in environmentally-powered computer systems. The model captures the effect of environmental conditions, the system's physical properties, and workload scheduling on performance. In evaluating our model, we distill the thermal effects that impact these systems using a small-scale prototype and a programmable incubator. We then leverage our model to show how considering these thermal effects in designing and operating environmentally-powered computer systems of varying scales can improve their energy-efficiency, performance, and availability.
There are the results of some municipal services actual specific cost for residential apartment building. These services consist of cold water supply system; drainage and sewage systems; electricity; collection and disposal of municipal solid waste system. Authors did not indicate the specific operating cost for hot water supply and heating systems because their cost was constant. Research period: from 1st quarter of 2018 year to the 2nd quarter of 2022 year. This period was acute phase of Covid-19 pandemic period. Authors have written the dynamics changes in the cost of considered services. Researchers have presented additional factors which affect to the unit cost of municipal services in this paper. There is a brief overview of management companies types which could be in municipal service system. Also it has been considered their capabilities and limitations in creating tariffs process. Authors have identified different trends in the engineering service unit cost changing process. This article could be interested for management companies and tariffs planning departments of public municipal service system in different parts of Russian Federation. Results which were presented in this paper could be used in predictive mathematical models of municipal services economical parts in critical as pandemic or other emergency situations.
Valery Makarenko, Volodymyr Gots, Volodymyr Pipa
et al.
It was established that the value of the critical stress SK for all experimental steels increases with the increase in the service life, and the impact viscosity decreases, which indicates structural embrittlement of pipe steels associated with their sudden flooding. It is shown that the new 20FA steel has the highest visco-plastic properties and resistance to brittle fracture, which is economically modified with a carbide-forming element (vanadium) and has a fine-grained structure and a low content of harmful impurities (sulfur, phosphorus). The microstrain of the α-Fe crystal lattice, as well as the quantitative decay of cementite and the redistribution of carbon between ferrite and pearlite, were evaluated by X-ray diffraction methods. The new steel grade 10FA is recommended for use in the construction of underground sewage systems and, for example, bridge structures, which are constantly under cyclic loads with simultaneous contact with a corrosive and aggressive environment. For the first time, the influence of the service life of pipelines on the hydrogen content and microcracks in pipe steels was determined.
Motahare Torshizi, Ali Nasirian, Hossein Eliasi
et al.
Using pressure reducing valves to reduce the pressure in water distribution systems to the minimum of required value is one of the most effective ways for leakage reduction. Valve opening/closing, switching a pump on/off and water consumption fluctuation by a large consumer cause transient flows. Interference between transient flow and a PRV with constant needle-valve setting may intensify pressure waves in WDS. Applying smart PRVs can limitpressure fluctuation. In this research, Input-output feedback linearization method has been used for smart PRV control. The results of this method have been compared with PRV with CNVS and proportional-integral-derivative controller. A theoretical network taken from references was used to evaluate the proposed methods. Network demands include normal consumers and an industrial large consumer. Water hammer caused by consumption variations, PRV with CNVS operation, IOFL method and PID controllers were modeled in Simulink. PRV outlet head fluctuation in PRV with CNVS is 18 to 28 m in PID controller and in IOFL method are 26 to 28 m. Also, the results showed that the IOFL method has smoother and less fluctuation than PID. Root-mean-square error for PRV outlet head in CNVS, PID controller and IOFL is 1.6, 0.32 and 0.28, respectively. Therefore, IOFL method has less error and better performance than PID. Also, this method has simpler computational operations by converting nonlinear system equations to linear equations.
Technology, Water supply for domestic and industrial purposes
D. Venkatramanan, Manish K. Singh, Olaolu Ajala
et al.
Synchronous generators and inverter-based resources are complex systems with dynamics that cut across multiple intertwined physical domains and control loops. Modeling individual generators and inverters is, in itself, a very involved activity and has attracted dedicated attention from power engineers and control theorists over the years. Control and stability challenges associated with increasing penetration of grid-following inverters have generated tremendous interest in grid-forming inverter technology. The envisioned coexistence of inverter technologies alongside rotating machines call for modeling frameworks that can accurately describe networked dynamics of interconnected generators and inverters across timescales. We put forth a comprehensive integrated system model for such a setting by: i) adopting a combination of circuit- and system-theoretic constructs, ii) unifying representations of three-phase signals across reference-frame transformations and phasor types, and iii) leveraging domain-level knowledge, engineering insights, and reasonable approximations. A running theme through our effort is to offer a clear distinction between physics-based models and the task of modeling. Among several insights spanning the spectrum from analytical to practical, we highlight how differential-algebraic-equation models and algebraic power-flow phasor models fall out of the detailed originating electromagnetic transient models.
Hasala Gallolu Kankanamalage, Yuandan Lin, Yuan Wang
Motivated by the regulator theory and adaptive controls, several notions on output stability in the framework of input-to-state stability (iss) were introduced for finite-dimensional systems. It turned out that these output stability notions are intrinsically different, reflecting different manners of how state variables may affect the transient behavior of output variables. In this work, we consider these output stability properties for delay systems. Our main objective is to illustrate how the various notions are related for delay systems and to provide the Razumikhin criteria for the output stability properties. The main results are also critical in developing the converse Lyapunov theorems of the output stability properties for delay systems
We study non-invariant Killing tensors with non-zero Nijenhuis torsion in the three-dimensional Euclidean space. Generalizing the corresponding integrable systems we construct two new families of superintegrable systems in $n$-dimensional Euclidean space.
We propose SmartON, a batteryless system that learns to wake up proactively at the right moment in order to detect events of interest. It does so by adapting the duty cycle to match the distribution of event arrival times under the constraints of harvested energy. While existing energy harvesting systems either wake up periodically at a fixed rate to sense and process the data, or wake up only in accordance with the availability of the energy source, SmartON employs a three-phase learning framework to learn the energy harvesting pattern as well as the pattern of events at run-time, and uses that knowledge to wake itself up when events are most likely to occur. The three-phase learning framework enables rapid adaptation to environmental changes in both short and long terms. Being able to remain asleep more often than a CTID (charging-then-immediate-discharging) wake-up system and adapt to the event pattern, SmartON is able to reduce energy waste, increase energy efficiency, and capture more events. To realize SmartON we have developed a dedicated hardware platform whose power management module activates capacitors on-the-fly to dynamically increase its storage capacitance. We conduct both simulation-driven and real-system experiments to demonstrate that SmartON captures 1X--7X more events and is 8X--17X more energy-efficient than a CTID system.
Due to the rapid increase of population in rural areas, specifically in Dakhlia Governorate, and the limited dwelling areas, the solid waste emanating either from stables, large animal stocks or agricultural waste causes hygienic problems, air pollution, water pollution, effects on the ecological balance and greater risk of dangerous fire. Anaerobic digestion is considered as one of the new trends in solid waste disposal. The anaerobic fermentation processes employed in/or by : 1- Industrial and municipal sewage treatment facilities. 2- Agricultural and animal biogas systems. 3- Garbage dumps/landfills. For industrial and municipal waste water treatment plants the prime objective is to stabilize the sludge and exploit the biogas as an energy carrier for fueling the thermal process. The anaerobic treatment of liquid manure from intensive livestock units should be carried out for the following reasons : (1) Breakdown of smells. (2) Production of biogas. (3) Improvement of fertilizer properties. For sanitary landfills/dump sites, utilization of anaerobic treatment permits the collection of the inevitably produced biogas in a beneficial form. The objective of this paper is to introduce the framework of the feasibility study for the evaluation of the biogas, produced from biofermentation of agricultural and animal waste and sewage sludge either for electricity generation or direct combustion. Also, the sludge produced from biofermentation would be evaluated as fertilizer or fodder additives as compared to its use in the raw form.
Michael T. Olexa, Tatiana Borisova, Jana Caracciolo
This handbook is designed to provide a summary of the principal federal and state (Florida) laws that directly or indirectly relate to agriculture. Because these laws are subject to constant revision, portions of the handbook could become outdated at any time. The reader should use it as a means to determine areas in which to seek more information and as a brief directory of agencies that can help answer more specific questions.
Unmanned aerial vehicles (UAVs), especially fixed-wing ones that withstand strong winds, have great potential for oceanic exploration and research. This paper studies a UAV-aided maritime data collection system with a fixed-wing UAV dispatched to collect data from marine buoys. We aim to minimize the UAV's energy consumption in completing the task by jointly optimizing the communication time scheduling among the buoys and the UAV's flight trajectory subject to wind effect, which is a non-convex problem and difficult to solve optimally. Existing techniques such as the successive convex approximation (SCA) method provide efficient sub-optimal solutions for collecting small/moderate data volume, whereas the solution heavily relies on the trajectory initialization and has not explicitly considered the wind effect, while the computational complexity and resulted trajectory complexity both become prohibitive for the task with large data volume. To this end, we propose a new cyclical trajectory design framework that can handle arbitrary data volume efficiently subject to wind effect. Specifically, the proposed UAV trajectory comprises multiple cyclical laps, each responsible for collecting only a subset of data and thereby significantly reducing the computational/trajectory complexity, which allows searching for better trajectory initialization that fits the buoys' topology and the wind. Numerical results show that the proposed cyclical scheme outperforms the benchmark one-flight-only scheme in general. Moreover, the optimized cyclical 8-shape trajectory can proactively exploit the wind and achieve lower energy consumption compared with the case without wind.
Motivated by the goal of having a building block in the direct design of data-driven controllers for nonlinear systems, we show how, for an unknown discrete-time bilinear system, the data collected in an offline open-loop experiment enable us to design a feedback controller and provide a guaranteed under-approximation of its basin of attraction. Both can be obtained by solving a linear matrix inequality for a fixed scalar parameter, and possibly iterating on different values of that parameter. The results of this data-based approach are compared with the ideal case when the model is known perfectly.