An approach to estimation of near-surface turbulence and CO2 transfer velocity from remote sensing data

The air–sea CO₂ exchange is primarily determined by the boundary-layer processes in the near-surface layer of the ocean since it is a water-side limited gas. As a consequence, the interfacial component of the CO₂ transfer velocity can be linked to parameters of turbulence in the near-surface layer of the ocean. The development of remote sensing techniques provides a possibility to quantify the dissipation of the turbulent kinetic energy in the near-surface layer of the ocean and the air–sea CO₂ transfer velocity on a global scale. In this work, the dissipation rate of the turbulent kinetic energy in the near-surface layer of the ocean and its patchiness has been linked to the air–sea CO₂ transfer velocity with a boundary-layer type model. Field observations of upper ocean turbulence, laboratory studies, and the direct CO₂ flux measurements are used to validate the model. The model is then forced with the TOPEX POSEIDON wind speed and significant wave height to demonstrate its applicability for estimating the distribution of the near-surface turbulence dissipation rate and gas transfer velocity for an extended (decadal) time period. A future version of this remote sensing algorithm will incorporate directional wind/wave data being available from QUIKSCAT, a now-cast wave model, and satellite heat fluxes. The inclusion of microwave imagery from the Special Sensor Microwave Imager (SSM/I) and the Synthetic Aperture Radar (SAR) will provide additional information on the fractional whitecap coverage and sea surface turbulence patchiness.     

Simulation of the mean zero-up-crossing wave period using artificial neural networks trained with a simulated annealing algorithm

The aim of this work was to develop a predictive model to forecast the mean zero-up-crossing wave periods (T _z ) for 3-hourly sea states at a location in the Pacific using artificial neural networks (ANNs). Seven multilayer ANNs were trained with a simulated annealing algorithm. The output of each trained ANN was used to estimate each of the seven parameters of a new distribution called the hepta-parameter spline proposed for the conditional distribution of T _z , given some mean zero-up-crossing wave periods and significant wave heights. After estimating the parameters of the distribution, the model was used to simulate and predict future values of T _z . Forecasting a sea state and developing the joint distribution of sea state characteristics with the help of the simulated characteristics are also discussed in this article.     

Performance Design of an Exhaust Superheater for Waste Heat Recovery of Construction Equipment

Although fuel cost has been the largest portion of annual operating costs of construction equipment, it is possible to save the energy and reduce cost using fuel economy enhancement technology. In this study, an organic Rankine cycle is applied to an excavator in order to recover waste heat, reproduce it into electrical energy, and consequently reduce the fuel consumption by 10 %. A design process was carried out to develop an exhaust gas superheater that recovers the waste heat from exhaust gas through a composite-dimensional thermal flow analysis. A one-dimensional code was developed to perform a size design for the exhaust gas superheater. The ranges for the major design parameters were determined to satisfy the target of the heat recovery, as well as the pressure drop at both fluid sides. Performance analysis was done through onedimensional design code results, which were compared with three-dimensional CFD analysis. By utilizing a 3D commercial code, the arrangement of the tubes was selected and the working fluid pressure drop was reduced through a detailed layout design. The design procedure was verified by a performance evaluation of the prototype, which yielded only a 7 % tolerance in heat recovery.     

Research on the coefficient of sound absorption in turbid water

China’s coastal waters are turbid and the properties of the seabed are complex. This negatively impacts the performance of underwater detection equipment. The properties of sound absorption in turbid water are not well understood. In this paper, the coefficient of sound absorption in turbid water was measured by the reverberation technique. All work was done in a reverberation barrel made of seamless aluminum. First, pure water was poured into the reverberation barrel and its reverberation time measured. Next, various concentrations of turbid water were poured into the barrel and their reverberation time measured. After all data had been gathered, the coefficient of sound absorption in turbid water of different concentrations was calculated. From this we determined a law of sound absorption in turbid water as summarized in the paper.     

How remote is remote pilotage?

“Today, the idea of allowing aircraft pilots to operate as they see fit, without any control from the land, is unthinkable. Will the same things apply to ships in twenty to thirty years’ time?”Current maritime pilotage regimes are clearly seen in some quarters as too restrictive and old fashioned. Change is “in the air” and VTS, pilotage, and the relationship between them cannot be immune to it. Subject to the attainment of the appropriate standards by both ships and their crews there is no practical reason why more flexible Vessel Traffic Management cannot be introduced. The required technology is largely available and, with the introduction of AIS, the required dynamic data can be available. Technical problems foreseen are believed capable of solution. The more significant obstacles to implementation are, therefore, largely political, commercial, organisational, and cultural. These issues are discussed in this paper taking into account the viewpoints of major stakeholders.     

Approximate algorithms for the discrete network design problem

The discrete network design problem is one of finding a set of feasible actions (projects) from among a collection of possible actions, that when implemented, optimizes some objective function(s). This is a combinatorial optimization problem that is very expensive to solve exactly. This paper proposes two algorithms for obtaining approximate solutions to the discrete network design problem with much less computational effeort. The computational savings are achieved by approximating the original problem with a new formulation which is easier to solve. The first algorithm proposed solves this approximate problem exactly, while the second is even more efficient, but provides only a near-optimal solution to the approximate problem. Experience with test problems indicates that these approximations can reduce the computational effort by a factor of 3–5, with little loss in solution accuracy.     

An analysis of the commuter departure time decision

Transportation planners and transit operators alike have become increasingly aware of the need to diffuse the concentration of peak period travel in an effort to improve gasoline economy and reduce peak load requirements. An evaluation of the potential effectiveness of strategies directed to achieve this end requires an understanding of factors which affect commuter trip timing decisions. The research discussed in this article addresses this particular problem through the development and estimation of a commuter departure time (to work) choice model.A number of conclusions were drawn based on the departure time model results and related analyses. It was found that work schedule flexibility, mode, occupation, income, age, and transportation level of service all influence departure time choice. The uncertainty in work arrival time and the consequences of various work arrival times may also be determinants of commuter departure time choice.The estimated model represents improvements over previous work in that it more explicitly considers work arrival time uncertainty and travelers' perceived loss associated with varying work arrival times, and additional socio-demographic factors which can potentially affect departure time choice. Furthermore, the estimated model includes consideration of transit commuters, in addition to single occupant auto and carpool work travelers. The inclusion of transit commuters represents a particularly important contribution for policy analysis, since the model could potentially be used to study the effect of service and employment policies on transit system peak load requirements.     

Research contributions to managing transit service reliability

Service reliability problems are a major concern shared by transit system users and operators. Unreliable service leads to additional vehicle requirements and higher operating costs; passengers suffer increased wait time and higher travel time uncertainty, leading to a general dissatisfaction with service and the possibility of seeking other means of transport. Because of the significance of this problem, considerable research attention has been focused in recent years on developing ways to improve service reliability. This paper examines contributions which have been made to managing transit service reliability. This topic encompasses the subjects of vehicle run time, run time variation, headway variation, passenger wait time, and reliability control. Both theoretical and empirical approaches have been undertaken, and each has contributed to our knowledge in addressing the overall problem. Significant contributions to the state-of-the-art are reported and the implications on present practice are discussed.     

结构动力学基于摄动法的高阶非线性随机有限元方法研究(英文)

Several algorithms were proposed relating to the development of a framework of the perturbation-based stochastic finite element method (PSFEM) for large variation nonlinear dynamic problems. For this purpose, algorithms and a framework related to SFEM based on the stochastic virtual work principle were studied. To prove the validity and practicality of the algorithms and framework, numerical examples for nonlinear dynamic problems with large variations were calculated and compared with the Monte-Carlo Simulation method. This comparison shows that the proposed approaches are accurate and effective for the nonlinear dynamic analysis of structures with random parameters.