OPTIMAL OPERATION OF MULTIPURPOSE RESERVOIRS IN SERIES: ROSEIRES AND SENNAR CASE STUDY

The Roseires-Sennar Dams System (RSDS) at lower part of Blue Nile River play a vital role in water supply to the irrigation schemes in Sudan. The existing rule curves for this system belong to 1925 and 1966 for Sennar and Roseires reservoirs, respectively. Introduction of new irrigation schemes, approved climate change impacts on Blue Nile River flow and upstream developments in Ethiopia as well as the heightening of the Roseires Dam from elevation 480 to 490 m.a.s.l have shown the RSDS is losing its efficiency in terms of fully supplying the water demands. The literature addresses the simulation of Roseires and Sennar dams, and tries to find the best coordinated rule curves through a limited number of operation rules to find optimal operating rules for reservoirs that minimize the impacts of new developments, water demand growth and climate change on water supply to various demands on Blue Nile River. Such decisions are locally optimal in best condition since they do not consider the storage and carry-over capability of reservoirs that can transfer the non-optimal (locally optimal) decisions to other time steps of planning horizon and creat shortages in other time steps. Therefore, aim of this research is to find optimal coordinating operation rules for Roseires and Sennar dams that through a non-linear multi-period optimization model that considers the conditions of climate change, flow regime and water demand as scenarios. Model is validated by comparison with observed reservoir operation during November 1999 till May 2000. Eighteen scenarios that cover the normal, dry and very dry flow regimes, along with three suggested crop patterns and climate change impact are analyzed. Results shows in normal conditions of flow, crop pattern 2 is the most recommended with more than 11 Billion USD marginal profit and fully supplying the water demand and 1530 GWh energy generation per annum. The coordinated rule curves have a totally different pattern of emptying and filling compared with existing ones. Rule curves change from one flow regime to another, which proves how change in conditions of the system has influence on optimal operation rules. Comparison of marginal profits with crop pattern 2 shows in three inflow conditions of normal, dry and very dry years multi-period optimization model could keep the marginal profits above 11 Billion USD, let’s say, 11,050, 11,056 and 11,042 Billion USD, respectively, which shows the robustness of model in dealing with all conditions and keeping the marginal profits not affected. However, the Roseires rule curves are different in these three condition, while Sennar rules curves are almost the same. Without climate change impact, model can manage to supply the water demands fully in all flow conditions. However, water supply reliability is affected by climate change with all crop patterns. Roseires-Sennar Dams system in a normal year under climate change can produce 10,688 Billion USD marginal profit and 1371 GWh per year energy. It shows that model could manage the system performance so that climate change decrease the marginal profit by 3.27%, while inflow is reduced by 25% and water demands and evaporation increased by 19%. Energy generation under climate change has decreased by 10.5%, which is the most affected sector. Crop pattern 2 and 3 are not suitable for climate change conditions since up to 65% deficit in water supply can happen if very dry year realizing with climate change. In very dry conditions crop pattern 1 is more suitable to be practiced.

Construction and Application of Reservoir Flood Control Operation Rules Using the Decision Tree Algorithm

Current conventional and optimal reservoir flood control operation methods insufficiently utilize historical reservoir operation data, which include rainfall, runoff generation, and inflow from the watershed, as well as the operational experience of decision makers over many years. Therefore, this study proposed and evaluated a new method for extracting reservoir flood control operation rules from historical operation data using the C4.5 algorithm. Thus, in this paper, the C4.5 algorithm is first introduced; then, the generation of the flood control operation dataset, the construction of decision tree-based (DT-based) rules, and the subsequent design of a real-time operating scheme are detailed. A case study of the Rizhao Reservoir is then employed to demonstrate the feasibility and even superiority of the operating scheme formulated using DT-based rules. Compared with previously proposed conventional and optimal reservoir operation methods, the DT-based method has the advantages of strong and convenient adaptability, enabling decision makers to effectively guide real-time reservoir operation.

LOCAL STUDIES OF ICE COVER EFFECTS ON DAM GATES

The experience of operation of surface emergency gates in ice-breaking conditions at a number of hydroelectric power plants has shown the insuffi cient eff ectiveness of the methods used to combat freezing of structures. The rules for technical operation of spillway dam gates in winter provide for heating of structures by slots, threshold and skin in conjunction with measures to maintain mines before construction. However, measures to heat gates and build mines are not always suffi ciently justifi ed and justifi ed. In order to obtain full-scale data and scientifi c information for the development of recommendations on operating and accounting modes during design, full-scale studies of stresses and defl ections in the load-bearing elements of the watershed gate of the hydroelectric power station were carried out. This article presents the results of fi eld studies in comparison with calculated values. As a result of the studies, information on the static operation of fl at gates in winter conditions is obtained, which is of theoretical and practical interest. The materials can be used to clarify technical operation rules and to clarify regulatory documents for the design of hydromechanical equipment at hydroelectric power stations.

Conditional Operation Rules For Optimal Conjunctive Use of Surface And Groundwater

The current study presents an efficient method for deriving precise operation rules from all subsystems of a distributed conjunctive use system (CUS), including aquifer, river, and reservoir. Distributed aquifer simulation has been performed using the URM method. Given that the historical flow time series can only represent one of the possible situations in the future and its use to determine the performance of the CUS is certainly not very reliable, in this study, river flow uncertainties are implicitly considered. To develop the operation rules, the time series of river flow were generated using autoregressive model. Then, the operation optimization model of the system was implemented with the objective function of minimizing water shortage for different river flow time series. 70% of the data was used for model training and 30% for model validation. Finally, using the decision tree algorithm (M5Rules), the conditional operation rules were extracted and compared with the single linear regression operation rules. Using five efficiency criteria CC, MAE, RMSE, RAE, and RRSE, the comparison of conditional and single linear regression operating rules has been done. The results showed that the the conditional operation rules reduces relative absolute error by a minimum of 39% and a maximum of 71%. If the system is operated according to the conditional rules, in the worst case, the amount of water shortage imposed will be 16.61 MCM over ten years.

Determination of fire frequency on CNG and LPG transport in Russia

Проанализированы статистические данные ФГБУ ВНИИПО МЧС России по пожарам на автомобилях с газобаллонным оборудованием (ГБО), по причинам пожаров на газобаллонных автомобилях (ГБА). Рассчитана средняя частота возникновения пожара для легковых, грузовых ГБА и автобусов с ГБО. Использованы сведения за 2015-2020 годы. There are reviewed and analyzed statistical data of FGBU VNIIPO EMERCOM of Russia on both number of fires in the Russian Federation depending on type of gas equipment (installations, appliances, devices), as a source of fire and fire causes. There are presented the results of evaluation of fire frequency in a year per one vehicle in operation and using compressed natural gas (CNG) or liquefied petroleum gas (LPG) as autogas (separate data on CNG and LPG vehicles are not presented, since the existing statistical base on fires is not subdivided by types of gas engine fuel used in vehicles) in Russia due to violation of arrangement and operation rules (VAOR) of gas equipment. The specified data is representative for enterprises for storage and maintenance of autogas vehicles. The data characterises the fire hazard of GBF, whereas such fire causes as arson, VAOR of vehicles, etc. are not actually implemented at the abovementioned enterprises. Conclusions on the causes of fires at BGF vehicles are drawn.

Path planning of spot welding robot based on multi-objective grey wolf algorithm

The path planning of traditional spot welding mostly uses manual teaching method. Here, a new model of path planning is established from two aspects of welding length and welding time. Then a multi-objective grey wolf optimization algorithm with density estimation (DeMOGWO) is proposed to solve multi-object discrete problems. The algorithm improves the coding method and operation rules, and sets the density estimation mechanism in the environment update. By comparing with other five algorithms on the benchmark problem, the simulation results show that DeMOGWO is competitive which takes into account both diversity and convergence. Finally, the DeMOGWO algorithm is used to solve the model established of path planning. The Pareto solution obtained can be used to guide the welding sequence of body-in-white(BIW) workpieces.

Can Managed Aquifer Recharge Overcome Multiple Droughts?

Frequent droughts, seasonal precipitation, and growing agricultural water demand in the Yakima River Basin (YRB), located in Washington State, increase the challenges of optimizing water provision for agricultural producers. Increasing water storage through managed aquifer recharge (MAR) can potentially relief water stress from single and multi-year droughts. In this study, we developed an aggregated water resources management tool using a System Dynamics (SD) framework for the YRB and evaluated the MAR implementation strategy and the effectiveness of MAR in alleviating drought impacts on irrigation reliability. The SD model allocates available water resources to meet instream target flows, hydropower demands, and irrigation demand, based on system operation rules, irrigation scheduling, water rights, and MAR adoption. Our findings suggest that the adopted infiltration area for MAR is one of the main factors that determines the amount of water withdrawn and infiltrated to the groundwater system. The implementation time frame is also critical in accumulating MAR entitlements for single-year and multi-year droughts mitigation. In addition, adoption behaviors drive a positive feedback that MAR effectiveness on drought mitigation will encourage more MAR adoptions in the long run. MAR serves as a promising option for water storage management and a long-term strategy for MAR implementation can improve system resilience to unexpected droughts.

A p-adic variant of Kontsevich–Zagier integral operation rules and of Hrushovski–Kazhdan style motivic integration

We prove that if two semi-algebraic subsets of ℚ p n {\mathbb{Q}_{p}^{n}} have the same p-adic measure, then this equality can already be deduced using only some basic integral transformation rules. On the one hand, this can be considered as a positive answer to a p-adic analogue of a question asked by Kontsevich–Zagier in the reals (though the question in the reals is much harder). On the other hand, our result can also be considered as stating that over ℚ p {\mathbb{Q}_{p}} , universal motivic integration (in the sense of Hrushovski–Kazhdan) coincides with the usual p-adic integration.

Development of a mathematical model for the process of modernization of a melon cleaning machine

The paper is devoted to the problem of increasing the efficiency of melon processing under limited production automation. Measures for equipment modernization should be carried out in accordance with the operation rules of each individual unit. In production conditions, all equipment, without exception, undergoes this process, while the corresponding documentation is drawn up, confirming the implementation of modernization within a certain time frame. In a competitive market environment, product quality is a causal factor for the sharp increase in risks for food industry enterprises. To produce quality and competitive products, you need equipment that helps to reduce costs. The disadvantages of most melon peeling designs are size instability in the thickness of the rind. The paper presents a solution to this drawback. This was achieved by changing the sharpening angle of the rind cutting knife. Research has been carried out to study the texture properties of “Mirzachulskaya” and “Raduzhnaya” melons. And also experiments on melon peeling based on the planning matrix of mathematical modeling. Based on the experiments, a model of the peeling process was constructed. The key factors to limit peeling waste were optimized. Calculations of the optimized parameters yielded the cutting knife sharpening angle of 40 degrees, a roller gap of 9 mm, as well as an average force applied of 1,375 N∙m. The data obtained can be used as a basis for the modernization of this machine for other melon varieties