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Journal articles on the topic "Transportation Mathematical models":
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Barceló, Jaume. "A survey of some mathematical programming models in transportation." Top 5, no. 1 (June 1997): 1–40. http://dx.doi.org/10.1007/bf02568528.
Jacob, C., F. Charras, X. Trosseille, J. Hamon, M. Pajon, and J. Y. Lecoz. "Mathematical models integral rating." International Journal of Crashworthiness 5, no. 4 (January 2000): 417–32. http://dx.doi.org/10.1533/cras.2000.0152.
Makhova, Larisa, Mark Haykin, Irina Glazkova, and Olga Domnina. "Development of Mathematical Models for Trucks and Cargo." Infrastructures 8, no. 2 (January 28, 2023): 17. http://dx.doi.org/10.3390/infrastructures8020017.
International trade allows countries to expand their markets and access goods and services that otherwise may not have been domestically available. As a result of international trade, the market is more competitive. This ultimately results in more competitive pricing and brings a cheaper product home to the consumer. The development of mathematical models to optimize the delivery of goods using a limited number of trucks is an urgent task for researchers around the world. The research goal was to use a developed mathematical model that allows one to optimize the performance of transportation tasks based on the selected parameters, both in terms of a particular truck and a fleet of trucks in the Russian region. The parameters (function, condition, cost, time, and quality) were set and an algorithm for the process of matching a specific truck and cargo was developed as part of the unit transportation task. A mathematical model has been developed for performing multiple freight tasks and operating a fleet of trucks, which considering such factors as cost, time, quality, and reputation, allows one to find an acceptable solution for a specific transportation task. A mathematical model was developed that considers such factors as cost, time, quality, and reputation, allowing one to find an acceptable solution for a particular transportation task. The simulation was performed in MATLAB 2018. The parameters of the simulations were a population size of 300, a maximum number of iterations of 2000, and a probability of selection of 0.85. From the 30 runs, the optional value was chosen as the best solution. The developed mathematical models have been tested for solving single and multiple transport problems under truck fleet simulation conditions. The results of the work can be used to optimize the operation of truck fleets in the Russian Federation and other countries.
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Cao, Junfang. "Mathematical Model and Algorithm of Multi-Index Transportation Problem in the Background of Artificial Intelligence." Journal of Advanced Transportation 2022 (April 26, 2022): 1–11. http://dx.doi.org/10.1155/2022/3664105.
The development of artificial intelligence has brought rapid changes to human life and brought great convenience to human activities. The development of various modes of transportation has also brought convenience to people’s travel and commodity transactions, but it has also added more issues that need to be carefully considered. Because of the diversification of transportation methods, transportation problems also arise many fields, such as air transportation, water transportation, and land transportation. The development of mathematical models and algorithms for transportation problems is also in full swing, and it is a major trend to introduce mathematical models and algorithms into the solution of transportation problems. This paper deals with the multi-index transportation problem by establishing a multi-index mathematical model and algorithm to find a scientific transportation method for the goods to be transported, so as to save the cost and time of transportation. Experiments show that the mathematical model established in this paper has high efficiency for solving the multi-index transportation problem. At the same time, the most suitable transportation method can also be selected for the transportation of goods, and the route planned by the mathematical model and algorithm can reduce the risk to 12.34%.
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Cao, Junfang. "Mathematical Model and Algorithm of Multi-Index Transportation Problem in the Background of Artificial Intelligence." Journal of Advanced Transportation 2022 (April 26, 2022): 1–11. http://dx.doi.org/10.1155/2022/3664105.
The development of artificial intelligence has brought rapid changes to human life and brought great convenience to human activities. The development of various modes of transportation has also brought convenience to people’s travel and commodity transactions, but it has also added more issues that need to be carefully considered. Because of the diversification of transportation methods, transportation problems also arise many fields, such as air transportation, water transportation, and land transportation. The development of mathematical models and algorithms for transportation problems is also in full swing, and it is a major trend to introduce mathematical models and algorithms into the solution of transportation problems. This paper deals with the multi-index transportation problem by establishing a multi-index mathematical model and algorithm to find a scientific transportation method for the goods to be transported, so as to save the cost and time of transportation. Experiments show that the mathematical model established in this paper has high efficiency for solving the multi-index transportation problem. At the same time, the most suitable transportation method can also be selected for the transportation of goods, and the route planned by the mathematical model and algorithm can reduce the risk to 12.34%.
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Zuo, Li. "Study on Mathematical Model of Freight Transportation Logistic Control." Applied Mechanics and Materials 178-181 (May 2012): 2573–76. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.2573.
Freight transportation activities in the present circumstances are closely related to a larger context of logistics decision-making, but logistic requirement is not relevant to all types of goods. Most existing freight transport demand models used for mode and route selection still focus only on the direct factors. This paper discusses the taxonomy of logistic and transport models, and the factors can be incorporated into freight transport demand models in order to improve the forecasting capability of the model.
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Zandieh, M., and S. Molla-Alizadeh-Zavardehi. "Synchronizing production and air transportation scheduling using mathematical programming models." Journal of Computational and Applied Mathematics 230, no. 2 (August 2009): 546–58. http://dx.doi.org/10.1016/j.cam.2008.12.022.
Naderi, B., A. Ahmadi Javid, and F. Jolai. "Permutation flowshops with transportation times: mathematical models and solution methods." International Journal of Advanced Manufacturing Technology 46, no. 5-8 (July 2, 2009): 631–47. http://dx.doi.org/10.1007/s00170-009-2122-8.
Patriksson, Michael. "Robust bi-level optimization models in transportation science." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 366, no. 1872 (March 10, 2008): 1989–2004. http://dx.doi.org/10.1098/rsta.2008.0007.
Mathematical programmes with equilibrium constraints (MPECs) constitute important modelling tools for network flow problems, as they place ‘what-if’ analyses in a proper mathematical framework. We consider a class of stochastic MPEC traffic models that explicitly incorporate possible uncertainties in travel costs and demands. In stochastic programming terminology, we consider ‘here-and-now’ models where decisions must be made before observing the uncertain parameter values and the responses of the network users; the objective is to minimize the expectation of the upper-level objective function. Such a model could, for example, be used to derive a fixed toll pricing scheme that provides the best revenue for a given network over a time period, where variations in traffic conditions and demand elasticities are described by distributions of parameters in the travel time and demand functions. We present new results on the stability of globally optimal solutions to perturbations in the probability distribution, establishing the robustness of the model. We also discuss penalization and discretization algorithms, the latter enabling the use of standard MPEC algorithms, and provide many future research avenues.
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Minaev, V. A., V. M. Pizengolts, A. O. Faddeev, A. Y. Bystryakov, E. V. Savenkova, and E. V. Kruglikova. "Modern information and mathematical models in construction industry." E3S Web of Conferences 116 (2019): 00051. http://dx.doi.org/10.1051/e3sconf/201911600051.
Building information modelling (BIM) – new technology of construction object information maintenance. It allows specifying influence of changes and risks made in it (including geodynamic) at all stages of lifecycle. Objects include products, building equipment, technological platform, the building, engineering, transportation networks and systems of building communication. The model expands possibilities of innovative technologies implementation, allowing creating reasoned economic decisions.
Dissertations / Theses on the topic "Transportation Mathematical models":
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Abdelghany, Ahmed F. "Dynamic micro-assignment of travel demand with activity/trip chains." Full text (PDF) from UMI/Dissertation Abstracts International Access restricted to users with UT Austin EID, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3023538.
Morales, Juan Carlos. "Planning Robust Freight Transportation Operations." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14107.
This research focuses on fleet management in freight transportation systems. Effective management requires effective planning and control decisions. Plans are often generated using estimates of how the system will evolve in the future; during execution, control decisions need to be made to account for differences between actual realizations and estimates. The benefits of minimum cost plans can be negated by performing costly adjustments during the operational phase. A planning approach that permits effective control during execution is proposed in this dissertation. This approach is inspired by recent work in robust optimization, and is applied to (i) dynamic asset management and (ii) vehicle routing problems.
In practice, the fleet management planning is usually decomposed in two parts; the problem of repositioning empty, and the problem of allocating units to customer demands. An alternative integrated dynamic model for asset management problems is proposed. A computational study provides evidence that operating costs and fleet sizes may be significantly reduced with the integrated approach. However, results also illustrate that not considering inherent demand uncertainty generates fragile plans with potential costly control decisions. A planning approach for the empty repositioning problem is proposed that incorporates demand and supply uncertainty using interval around nominal forecasted parameters. The intervals define the uncertainty space for which buffers need to be built into the plan in order to make it a robust plan. Computational evidence suggests that this approach is tractable.
The traditional approach to address the Vehicle Routing Problem with Stochastic Demands (VRPSD) is through cost expectation minimization. Although this approach is useful for building routes with low expected cost, it does not directly consider the maximum potential cost that a vehicle might incur when traversing the tour. Our approach aims at minimizing the maximum cost. Computational experiments show that our robust optimization approach generates solutions with expected costs that compare favorably to those obtained with the traditional approach, but also that perform better in worst-case scenarios. We also show how the techniques developed for this problem can be used to address the VRPSD with duration constraints.
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Kim, Kihong. "Recent Advances in Activity-Based Travel Demand Models for Greater Flexibility." PDXScholar, 2018. https://pdxscholar.library.pdx.edu/open_access_etds/4225.
Most existing activity-based travel demand models are implemented in a tour-based microsimulation framework. Due to the significant computational and data storage benefits, the demand microsimulation allows a greater amount of flexibility in terms of demographic market segmentation, temporal scale, and spatial resolution, and thus the models can represent a wider range of travel behavior aspects associated with various policies and scenarios. This dissertation proposes three innovative methodologies, one for each of the three key dimensions, to fulfill the greater level of details toward a more mature state of activity-based travel demand models.
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Xu, Suxiu, and 徐素秀. "Truthful, efficient auctions for transportation procurement." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206443.
Transportation procurement problem (TPP) is the problem of setting transportation service prices, delivery timing and quantity, and controlling costs and capacity to reduce empty movements and improve market efficiency. The purchase of transportation service is traditionally achieved using a request for proposal and long-term contracts. However, as business relationships become ever more flexible and dynamic, there has been an increasing need to hedge the risks of traditional transportation procurement such as entrance of new carriers and sudden drop in fuel price. This thesis proposes a holistic aution-based solution for the TPP.
Four typical scenarios are investigated. The first scenario incorporates bilateral bidding into auction mechanism design for multi-unit TPP. This scenario considers one-sided Vickrey-Clarke-Groves (O-VCG) combinatorial auctions for a complex transportation marketplace with multiple lanes. This scenario then designs three alternative multi-unit trade reduction (MTR) mechanisms for the bilateral exchange transportation marketplace where all the lanes are partitioned into distinct markets. Proposed mechanisms ensure incentive compatibility, individual rationality, budget balance and asymptotical efficiency.
The second scenario presents a double auction model for the TPP in a dynamic single-lane transportation environment. This scenario first addresses the TPP in a transportation spot market with stochastic but balanced or “symmetric” demand and supply. A periodic sealed double auction (PSDA) is proposed. This scenario then devises a modified PSDA (M-PSDA) to address the TPP with “asymmetric” demand and supply. The auctioneer is likely to gain higher profits from setting a relatively short auction length. However, it is optimal to run the auction (either PSDA or MPSDA) with a relatively large auction length, when maximizing either the social welfare or the utility of shippers and carriers (agents). When the degree of supply-demand imbalance is low, the auctioneer’s myopic optimal expected profit under supply-demand imbalance is larger than that under symmetric demand and supply.
This third scenario presents an auction-based model for the TPP in make-toorder systems. The optimality of dynamic base-stock type (S(x)-like policy) is established. The optimal allocation can be achieved by running an O-VCG auction or a first-price auction with closed-form reserve prices. By mild technical modifications, the results derived in the infinite horizon case can all be extended to the finite horizon case.
The fourth scenario proposes allocatively efficient auction mechanisms for the distributed transportation procurement problem (DTPP), which is generally the problem of matching demands and supplies over a transportation network. This scenario constructs an O-VCG combinatorial auction for the DTPP where carriers are allowed to bid on bundles of lanes. To simplify the execution of auction, this scenario next proposes a primal-dual Vickrey (PDV) auction based on insights from the known Ausubel auctions and the primal-dual algorithm. The PDV auction realizes VCG payments and truthful bidding under the condition of seller-submodularity, which implies that the effect of each individual carrier is decreasing when the coalition increases. published_or_final_version Industrial and Manufacturing Systems Engineering Doctoral Doctor of Philosophy
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Fischer, Manfred M. "Computational Neural Networks: An attractive class of mathematical models for transportation research." WU Vienna University of Economics and Business, 1997. http://epub.wu.ac.at/4158/1/WSG_DP_5797.pdf.
Zhang, Lu, and 張露. "An integrated approach to empty container repositioning and vessel routing in marine transportation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206354.
Cramer, Jay Alan 1957. "APPLICATION OF POLYHEDRAL DYNAMICS TO PEDESTRIAN ACCIDENTS (TRANSPORTATION)." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/277115.
Qin, Jiefeng. "System dynamics representation of catastrophe and its application to transportation." Thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-05042010-020251/.
Jiang, Yu, and 姜宇. "Reliability-based transit assignment : formulations, solution methods, and network design applications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/207991.
This dissertation is about games with a continuum of players and horizontal differentiation. The first chapter explains how price dispersion can be a feature of a competitive market with homogenous information and production costs. The second chapter extends the study to group consumption. The third chapter is about multiple equilibria in urban transportation. Doctorat en Sciences économiques et de gestion info:eu-repo/semantics/nonPublished
National Research Council (U.S.). Transportation Research Board., ed. Transportation logistics. Washington, D.C: Transportation Research Board, National Research Council, 1987.
1958-, Labbé Martine, North Atlantic Treaty Organization. Scientific Affairs Division., and NATO Advanced Study Institute on Operations Research and Decision Aid Methodologies in Traffic and Transportation Management (1997 : Balatonfüred, Hungary), eds. Operations research and decision aid methodologies in traffic and transportation management. Berlin: Springer, 1998.
Keith, Nancy K. Estimating aggregation errors in transportation problems. West Lafayette, Ind: Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1986.
Book chapters on the topic "Transportation Mathematical models":
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Daganzo, Carlos F. "Mathematical Specification of Transportation Models." In Measuring the Unmeasurable, 663–78. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5079-5_28.
Schmand, Daniel. "Recent Developments in Mathematical Traffic Models." In Dynamics in Logistics, 71–87. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88662-2_4.
AbstractPredictions such as forecasts of congestion effects in transportation networks can be based on complex simulations that include many aspects of actual transportation systems. On the other hand, rigorous mathematical traffic models give rise to theoretical analyses, very general statements, and various traffic optimization opportunities. There has been a huge development in the last years to make mathematical traffic models more realistic. This chapter provides an overview of the mathematical traffic models developed recently and some state-of-the-art results.
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Crainic, Teodor Gabriel. "Service Design Models for Rail Intermodel Transportation." In Lecture Notes in Economics and Mathematical Systems, 53–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92944-4_4.
Kim, Daeki, and Cynthia Barnhart. "Transportation Service Network Design: Models and Algorithms." In Lecture Notes in Economics and Mathematical Systems, 259–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-85970-0_13.
Moiseenko, Valentin, Volodymyr Butenko, Oleksandra Golovko, Oleksandr Kameniev, and Vitalii Gaievskyi. "Mathematical Models of the System Integration and Structural Unification of Specialized Railway Computer Systems." In ICTE in Transportation and Logistics 2019, 129–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39688-6_18.
Bąk, Marcin, Piotr Patrosz, Paweł Śliwiński, Paweł Załuski, and Mykola Karpenko. "Comparison of Mathematical Models of Torque Transmitted by Multi-disc Wet Clutch with Experimental Results." In TRANSBALTICA XIII: Transportation Science and Technology, 383–92. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-25863-3_36.
Bertazzi, Luca, and Maria Grazia Speranza. "Models and Algorithms for the Minimization of Inventory and Transportation Costs: A Survey." In Lecture Notes in Economics and Mathematical Systems, 137–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-58568-5_7.
Katin, Viktor, Vladimir Kosygin, Midkhat Akhtiamov, and Igor Vol’khin. "Mathematical Models of the Output of Major Pollutants in the Process of Burning Water Fuel Oil Emulsions in Boiler Plants." In International Scientific Conference Energy Management of Municipal Transportation Facilities and Transport EMMFT 2017, 987–97. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70987-1_107.
Conference papers on the topic "Transportation Mathematical models":
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Jensen, Emily, Maya Luster, Hansol Yoon, Brandon Pitts, and Sriram Sankaranarayanan. "Mathematical Models of Human Drivers Using Artificial Risk Fields." In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2022. http://dx.doi.org/10.1109/itsc55140.2022.9922389.
Grebennik, Igor, Olga Chorna, and Inna Urniaieva. "Distribution of Permutations with Different Cyclic Structure in Mathematical Models of Transportation Problems." In 2022 12th International Conference on Advanced Computer Information Technologies (ACIT). IEEE, 2022. http://dx.doi.org/10.1109/acit54803.2022.9913183.
Huang, Kai, Yu Gu, Haoming Yang, Kun An, and Zhiyuan Liu. "Mathematical Models for the Matching and Routing Problem of Customized Bus Service with Multiple Origins and Destinations." In 17th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784480915.288.
He, Linwei, Dawei Hu, Xiqiong Chen, and Xu Zhou. "Comparison of Various Mathematical Models for Vehicle Routing Problem with Simultaneous Pickups and Deliveries with Time Window." In 22nd COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2022. http://dx.doi.org/10.1061/9780784484265.292.
Kostogryzov, Andrey, Vladimir Krylov, Andrey Nistratov, George Nistratov, Vladimir Popov, and Pavel Stepanov. "Mathematical Models and Applicable Technologies to Forecast, Analyze, and Optimize Quality and Risks for Complex Systems." In First International Conference on Transportation Information and Safety (ICTIS). Reston, VA: American Society of Civil Engineers, 2011. http://dx.doi.org/10.1061/41177(415)107.
Chi, Xiaopeng. "A Multivariate Decision-Making Mathematical Models Based on the Fuzzy Mathematics Theory and Comprehensive Coordination of Statistics for Evaluating the Quality of Physical Education." In 2015 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS). IEEE, 2015. http://dx.doi.org/10.1109/icitbs.2015.12.
Lyapin, Sergey, Yulia Rizaeva, Dmitry Kadasev, and Irina Kadaseva. "Models for Ensuring the Minimum Arrival Time of Accident Response Services in Intelligent Transportation and Logistics System." In 2020 2nd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). IEEE, 2020. http://dx.doi.org/10.1109/summa50634.2020.9280810.
Ristevski, Stefan, and Melih Çakmakcı. "Mathematical Model for Coordinated Motion of Modular Mechatronic Devices (MechaCells)." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9896.
Manufacturing techniques have advanced exponentially in recent years, providing means for micro even nano scale manufacturing of different structures. Mechanical and electrical components are being manufactured at micro/nano scale, producing amazing opportunities in micro/nano modular robot development, for modules that are smaller and more powerful. Development of mathematical models for such modular devices is an important step in the design and development of control strategies for coordinated movement. A mathematical model for modular mechatronic device, MechaCell was developed, in which the interaction forces between module–workpiece are modeled as the disturbance to be compensated by the closed loop position controller for each device. Experiments with an actual workpiece are conducted and our mathematical model was validated. Our future work will include development of better control strategies for coordinated motion and object transportation and caging stratifies.
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Yuan, Qing, Zhiming Wu, Wang Li, Bo Yu, and Changchun Wu. "Comparative Study on Atmospheric Temperature Models for the Buried Hot Oil Pipeline." In 2018 12th International Pipeline Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/ipc2018-78451.
In previous studies, the atmospheric temperature was generally assumed to be constant during a period (commonly a month) for the numerical simulation on the buried hot oil pipeline. The rationality of this assumption is controversial due to the absence of quantitative results, and thus it needs to be further verified or investigated to make atmospheric temperature approximation more convincing. In this study, based on the changing trend of actual atmospheric temperature, three mathematical models are established and their expressions are presented according to different approximations. And the relationships among these three expressions are obtained by utilizing mathematical derivation. On the basis of three atmospheric temperature models, the weakly unsteady single oil transportation and strongly unsteady batch transportation are numerically simulated, respectively. According to numerical results, the oil temperature at the pipeline ending point and the soil temperature field are compared for these three models. In order to make comparisons more convincing, the influences of the physical properties of crude oil, operation parameters, pipeline parameters and pipeline environments on the deviations of numerical results are compared and analyzed. Finally, based on all comparisons on the deviations of numerical results, the conclusions are drawn, which can provide beneficial reference for the choice of atmospheric temperature models in future numerical simulation study on the buried hot oil pipeline.
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Abdou, Hesham A. M. "Managing of a Strategic Crude Oil Pipeline for Maximum Transportation Capacity." In ASME 2013 India Oil and Gas Pipeline Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/iogpc2013-9802.
The aged crude oil pipeline; 16″ × 166 km since November 1984, extends from Meleiha field at western desert to El-Hamra terminal at coast of the Mediterranean sea. Its original capacity was 100,000 BOPD using two pumping stations; one at Meleiha and the other is a boosting station, 83 km far from Meleiha. Planned pumped flow rate increased to 177,000 BOPD at the time that Maximum Allowable Working Pressure (MAWP) reduced from 1440 psi to 950 psi. This paper shows managing procedures led to pumping higher flow rate without exceeding MAWP, where two solutions to accommodate such increase in production were applied; firstly by looping the existing pipeline with a (16″ × 56 km), secondly by using a Drag Reducing Agent (DRA), so that could reduce hydraulic friction losses and Total Dynamic Pressure (TDP) in the system and could pumped more with reduced initial pumping pressure at Meleiha. So, the intermediate station was temporarily abandoned. Mathematical models are designed to simulate pumping operation through the whole system, where TDP is predicted for the three pipeline cases: 1- normal case without both looping & DRA. 2- case without DRA & with looping. 3- case with both looping & DRA. Laws of hydraulics are applied with the deduced formula represents performance of DRA in which percentage of drop in pressure losses is modeled as a function of DRA dose in ppm. Close agreement is remarked between values of the deduced theoretical values and actual values obtained for TDP, confirming validity of such mathematical models.
Reports on the topic "Transportation Mathematical models":
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Perdigão, Rui A. P. Beyond Quantum Security with Emerging Pathways in Information Physics and Complexity. Synergistic Manifolds, June 2022. http://dx.doi.org/10.46337/220602.
Information security and associated vulnerabilities have long been a pressing challenge, from the fundamental scientific backstage to the frontline across the most diverse sectors of society. At the tip of the iceberg of this problem, the citizens immediately feel that the reservation of privacy and the degradation of the quality and security of the information and communication on which they depend for the day-to-day activities, already of crucial relevance, are at stake. Naturally though, the challenges do not end there. There is a whole infrastructure for storing information, processing and communication, whose security and reliability depend on key sectors gearing modern society – such as emergency communication systems (medical, civil and environmental protection, among others), transportation and geographic information, the financial communications systems at the backbone of day-to-day transactions, the information and telecommunications systems in general. And crucially the entire defence ecosystem that in essence is a stalwart in preventing our civilisation to self-annihilate in full fulfilment of the second principle of thermodynamics. The relevance of the problem further encompasses the preservation of crucial values such as the right to information, security and integrity of democratic processes, internal administration, justice, defence and sovereignty, ranging from the well-being of the citizen to the security of the nation and beyond. In the present communication, we take a look at how to scientifically and technically empower society to address these challenges, with the hope and pragmatism enabled by our emerging pathways in information physics and complexity. Edging beyond classical and quantum frontiers and their vulnerabilities to unveil new principles, methodologies and technologies at the core of the next generation system dynamic intelligence and security. To illustrate the concepts and tools, rather than going down the road of engineered systems that we can ultimately control, we take aim at the bewildering complexity of nature, deciphering new secrets in the mathematical codex underlying its complex coevolutionary phenomena that so heavily impact our lives, and ultimately bringing out novel insights, methods and technologies that propel information physics and security beyond quantum frontiers.
