The Experts below are selected from a list of 128691 Experts worldwide ranked by ideXlab platform
Sheng Liu - One of the best experts on this subject based on the ideXlab platform.
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Modeling of Ship Collision Risk Based on Cloud Model
IEEE Access, 2020Co-Authors: Hongdan Liu, Lanyong Zhang, Sheng LiuAbstract:Existing models for assessing ship collision Risk involve complex calculations that complicate the simultaneous qualitative and quantitative analysis of the factors affecting ship navigation safety. Therefore, these models often exhibit slow generation of the Risk index and evaluation results with reduced accuracy. To resolve these issues, we model the ship collision Risk based on the cloud model theory. Specifically, we select “distance of closest point of approach (DCPA)” and “time to closest point of approach (TCPA)” as the main factors affecting the ship collision Risk and analyze the data of DCPA, TCPA, and collision Risk index (CRI) based on their cloud models. By combining these analyses with a double-condition-single-rule generator, we construct a cloud model for ship collision Risk and finally develop a cloud model-based inference engine system to assess ship collision Risk. This engine allows us to establish different ship collision Risk analysis models according to the scenario encountered by the ship, which can be used to verify the feasibility of the proposed algorithm for ship collision Risk Modeling. Through comparisons with traditional ship collision Risk models, the proposed ship collision Risk model is found to be superior owing to its simple implementation, accurate results, and shorter time required to generate the Risk model. The model established in this study enables the crew to determine the key objects to be avoided in case of potential collision with multiple ships. At last,analysis and research of cloud model ship collision Risk based on global sensitivity and uncertainty are done to reduce the dimension of the Risk parameters and show the main factors of unstable collision Risk,therefore,the uncertain results in the calculation of the degree of danger are avoided, some reasonable suggestions are proposed for real navigation safety. the maritime pilot can make correct decisions promptly to reduce or avoid the occurrence of collision accidents.
Hongdan Liu - One of the best experts on this subject based on the ideXlab platform.
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Evaluation Modeling Establishment for the Risk Degree of Ship Collision
Application of Intelligent Systems in Multi-modal Information Analytics, 2020Co-Authors: Hongdan Liu, Yue SunAbstract:Aim to solve the problem that the qualitative and quantitative the influencing factors of ship navigation safety is to be difficult to merger analysis, due to the large amount of calculation and complicated realization process of ship collision Risk model, the strategy of Risk degree of ship collision evaluation based on the cloud model theory is introduced, the data of cloud model of DCPA (Distance to closed point of approach), TCPA (Time to closest point of approach) and CRI (Collision Risk Level) is formed to reasoning Risk degree of ship collision based on double conditional single rule generator. According to the different ship encounter situation, the order is sorted on the collision Risk degree between own and target ship by the cloud Modeling inference mechanism. Thus, the availability and feasibility of this algorithm are verified in ship collision Risk Modeling. The establishment of this model enables the crew members to determine the key collision avoidance objects in time, to reduce or avoid the occurrence of collision accidents at the source.
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Modeling of Ship Collision Risk Based on Cloud Model
IEEE Access, 2020Co-Authors: Hongdan Liu, Lanyong Zhang, Sheng LiuAbstract:Existing models for assessing ship collision Risk involve complex calculations that complicate the simultaneous qualitative and quantitative analysis of the factors affecting ship navigation safety. Therefore, these models often exhibit slow generation of the Risk index and evaluation results with reduced accuracy. To resolve these issues, we model the ship collision Risk based on the cloud model theory. Specifically, we select “distance of closest point of approach (DCPA)” and “time to closest point of approach (TCPA)” as the main factors affecting the ship collision Risk and analyze the data of DCPA, TCPA, and collision Risk index (CRI) based on their cloud models. By combining these analyses with a double-condition-single-rule generator, we construct a cloud model for ship collision Risk and finally develop a cloud model-based inference engine system to assess ship collision Risk. This engine allows us to establish different ship collision Risk analysis models according to the scenario encountered by the ship, which can be used to verify the feasibility of the proposed algorithm for ship collision Risk Modeling. Through comparisons with traditional ship collision Risk models, the proposed ship collision Risk model is found to be superior owing to its simple implementation, accurate results, and shorter time required to generate the Risk model. The model established in this study enables the crew to determine the key objects to be avoided in case of potential collision with multiple ships. At last,analysis and research of cloud model ship collision Risk based on global sensitivity and uncertainty are done to reduce the dimension of the Risk parameters and show the main factors of unstable collision Risk,therefore,the uncertain results in the calculation of the degree of danger are avoided, some reasonable suggestions are proposed for real navigation safety. the maritime pilot can make correct decisions promptly to reduce or avoid the occurrence of collision accidents.
Bernard Mcgarvey - One of the best experts on this subject based on the ideXlab platform.
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Quantitative Risk Modeling in aseptic manufacture.
PDA journal of pharmaceutical science and technology, 2006Co-Authors: Edward C. Tidswell, Bernard McgarveyAbstract:Expedient Risk assessment of aseptic manufacturing processes offers unique opportunities for improved and sustained assurance of product quality. Contemporary Risk assessments applied to aseptic manufacturing processes, however, are commonly handicapped by assumptions and subjectivity, leading to inexactitude. Quantitative Risk Modeling augmented with Monte Carlo simulations represents a novel, innovative, and more efficient means of Risk assessment. This technique relies upon fewer assumptions and removes subjectivity to more swiftly generate an improved, more realistic, quantitative estimate of Risk. The fundamental steps and requirements for an assessment of the Risk of bioburden ingress into aseptically manufactured products are described. A case study exemplifies how quantitative Risk Modeling and Monte Carlo simulations achieve a more rapid and improved determination of the Risk of bioburden ingress during the aseptic filling of a parenteral product. Although application of quantitative Risk Modeling is described here purely for the purpose of process improvement, the technique has far wider relevance in the assisted disposition of batches, cleanroom management, and the utilization of real-time data from rapid microbial monitoring technologies.
Lena Q - One of the best experts on this subject based on the ideXlab platform.
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high resolution measurement and mapping of tungstate in waters soils and sediments using the low disturbance dgt sampling technique
Journal of Hazardous Materials, 2016Co-Authors: Dongxing Guan, Paul N Williams, Jun Luo, Lena QAbstract:Increasing tungsten (W) use for industrial and military applications has resulted in greater W discharge into natural waters, soils and sediments. Risk Modeling of W transport and fate in the environment relies on measurement of the release/mobilization flux of W in the bulk media and the interfaces between matrix compartments. Diffusive gradients in thin-films (DGT) is a promising passive sampling technique to acquire such information. DGT devices equipped with the newly developed high-resolution binding gels (precipitated zirconia, PZ, or ferrihydrite, PF, gels) or classic/conventional ferrihydrite slurry gel were comprehensively assessed for measuring W in waters. (Ferrihydrite)DGT can measure W at various ionic strengths (0.001-0.5molL(-1) NaNO3) and pH (4-8), while (PZ)DGT can operate across slightly wider environmental conditions. The three DGT configurations gave comparable results for soil W measurement, showing that typically W resupply is relatively poorly sustained. 1D and 2D high-resolution W profiling across sediment-water and hotspot-bulk media interfaces from Lake Taihu were obtained using (PZ)DGT coupled with laser ablation ICP-MS measurement, and the apparent diffusion fluxes across the interfaces were calculated using a numerical model.
Michael G Lutomski - One of the best experts on this subject based on the ideXlab platform.
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the use of quantitative Risk assessment in the operations phase of space missions
Safety Design for Space Operations, 2013Co-Authors: Michael G LutomskiAbstract:This chapter provides an understanding of quantitative Risk assessment as it is applied in the operational phase of complex aerospace missions. It addresses the application of a quantitative Risk model that has already been built and reviewed for a project or program that is in the operations phase. Several aerospace examples are discussed, but the focus of the chapter is the use of Risk Modeling in the operational phase of the International Space Station (ISS) program. Examples are presented to highlight the application and flexibility of Risk assessments or trade studies in the operations phase. Operational Risk trades account for nearly all of the Risk analysis performed for the ISS program.
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The Use of Quantitative Risk Assessment in the Operations Phase of Space Missions
Safety Design for Space Operations, 2013Co-Authors: Michael G LutomskiAbstract:This chapter provides an understanding of quantitative Risk assessment as it is applied in the operational phase of complex aerospace missions. It addresses the application of a quantitative Risk model that has already been built and reviewed for a project or program that is in the operations phase. Several aerospace examples are discussed, but the focus of the chapter is the use of Risk Modeling in the operational phase of the International Space Station (ISS) program. Examples are presented to highlight the application and flexibility of Risk assessments or trade studies in the operations phase. Operational Risk trades account for nearly all of the Risk analysis performed for the ISS program.
