Wave forces on oscillating bodies at small forward speed

A theoretical investigation is carried out to study the interactions between waves and large offshore structures at small forward speed. First order added mass, radiation damping and exciting forces as well as dynamic responses of rigid structures at small forward speed are presented. Second order mean drift forces at forward speed and low frequency wave drift damping are also presented. An asymptotic analysis of the mean drift force on a vertical cylinder at small forward speed in long waves is first carried out. The mean drift force is obtained analytically by using a far field method, and the wave drift damping is estimated and discussed. For arbitrary bodies, a perturbation theory on the basis of a small forward speed parameter is proposed and developed. The fluid flow around the body is solved in terms of a zero forward speed problem and a forward speed correction problem. The latter is linearly proportional to the forward speed. A novel multipole expansion is presented for the velocity potential of zero forward speed motion. The expressions are valid for both completely submerged bodies and surface piercing bodies. A computer program is implemented, based on the small forward speed theory. Two coupled numerical methods are utilized. Solutions of the first order dynamic motions, second order mean drift forces and wave drift damping are presented for several floating and submerged horizontal cylinders. It is observed that the influence of the small forward speed on the second order hydrodynamic forces is larger than that on the first order hydrodynamic forces; and that among the first order forces, the influence on the exciting forces is larger than that on the added mass and radiation damping

Geographic routing in duty-cycled industrial wireless sensor networks with radio irregularity

Industrial wireless sensor networks (IWSNs) are required to provide highly reliable and real-time transmission. Moreover, for connected K-neighborhood (CKN) sleep scheduling-based duty-cycled IWSNs in which the network lifetime of IWSNs can be prolonged, the two-phase geographic greedy forwarding (TPGF) geographic routing algorithm has attracted attention due to its unique transmission features: multi path, shortest path, and hole bypassing. However, the performance of TPGF in CKN-based duty-cycled IWSNs with radio irregularity is not well investigated in the literature. In this paper, we first evaluate the impact of radio irregularity on CKN-based duty-cycled IWSNs. Furthermore, we investigate the routing performance of TPGF in CKN-based duty-cycled IWSNs with radio irregularity, in terms of the number of explored routing paths as well as the lengths of the average and shortest routing paths. Particularly, we establish the upper bound on the number of explored routing paths. The upper bound is slightly relaxed with radio irregularity compared with without radio irregularity; however, it is bounded by the number of average 1-hop neighbors in always-on IWSNs. With extensive simulations, we observe that the cross-layer optimized version of TPGF (i.e., TPFGPlus) finds reliable transmission paths with low end-to-end delay, even in CKN-based duty-cycled IWSNs with radio irregularity

Power generation expansion optimization model considering multi-scenario electricity demand constraints: a case study of Zhejiang Province, China

Reasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%). Different key performance indicators (KPI) differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML) produces the optimal power development path, as it provides the lowest discounted cost

Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles.

Articulated wheel loaders used in the construction industry are heavy vehicles and have poor stability and a high rate of accidents because of the unpredictable changes of their body posture, mass and centroid position in complex operation environments. This paper presents a novel distributed multi-sensor system for real-time attitude estimation and stability measurement of articulated wheel loaders to improve their safety and stability. Four attitude and heading reference systems (AHRS) are constructed using micro-electro-mechanical system (MEMS) sensors, and installed on the front body, rear body, rear axis and boom of an articulated wheel loader to detect its attitude. A complementary filtering algorithm is deployed for sensor data fusion in the system so that steady state margin angle (SSMA) can be measured in real time and used as the judge index of rollover stability. Experiments are conducted on a prototype wheel loader, and results show that the proposed multi-sensor system is able to detect potential unstable states of an articulated wheel loader in real-time and with high accuracy

Function value-based multi-objective optimisation of reheating furnace operations using Hooke-Jeeves algorithm

Improved thermal efficiency in energy-intensive metal-reheating furnaces has attracted much attention recently in efforts to reduce both fuel consumption, and CO2 emissions. Thermal efficiency of these furnaces has improved in recent years (through the installation of regenerative or recuperative burners), and improved refractory insulation. However, further improvements can still be achieved through setting up reference values for the optimal set-point temperatures of the furnaces. Having a reasonable expression of objective function is of particular importance in such optimisation. This paper presents a function value-based multi-objective optimisation where the objective functions, which address such concerns as discharge temperature, temperature uniformity, and specific fuel consumption, are dependent on each other. Hooke-Jeeves direct search algorithm (HJDSA) was used to minimise the objective functions under a series of production rates. The optimised set-point temperatures were further used to construct an artificial neural network (ANN) of set-point temperature in each control zone. The constructed artificial neural networks have the potential to be incorporated into a more advanced control solution to update the set-point temperatures when the reheating furnace encounters a production rate change. The results suggest that the optimised set-point temperatures can highly improve heating accuracy, which is less than 1 °C from the desired discharge temperature

Measuring denitrification and the N2_{2}O:(N2_{2}O + N2_{2}) emission ratio from terrestrial soils

Denitrification, a significant pathway of reactive N-loss from terrestrial soils, impacts on agricultural production and the environment. Net production and emission of the denitrification product nitrous oxide (N$_{2}$O) is readily quantifiable, but measuring denitrification\u27s final product, dinitrogen (N$_{2}$), against a high atmospheric background remains challenging. This review examines methods quantifying both N$_{2}$ and N$_{2}$O emissions, based on inhibitors, helium/O$_{2}$ atmosphere exchange, and isotopes. These methods are evaluated regarding their capability to account for pathways of N$_{2}$ and N$_{2}$O production and we suggest quality parameters for measuring denitrification from controlled environments to the field scale. Our appraisal shows that method combinations, together with real-time monitoring and soil-gas diffusivity modelling, have the potential to significantly improve our quantitative understanding for denitrification from upland soils. Requirements for instrumentation and experimental setups however highlight the need to develop more mobile and easily accessible field methods to constrain denitrification from terrestrial soils across scales

Integrated modelling of crop production and nitrate leaching with the Daisy model

An integrated modelling strategy was designed and applied to the Soil-Vegetation-Atmosphere Transfer model Daisy for simulation of crop production and nitrate leaching under pedo-climatic and agronomic environment different than that of model original parameterisation. The points of significance and caution in the strategy are: • Model preparation should include field data in detail due to the high complexity of the soil and the crop processes simulated with process-based model, and should reflect the study objectives. Inclusion of interactions between parameters in a sensitivity analysis results in better account for impacts on outputs of measured variables. • Model evaluation on several independent data sets increases robustness, at least on coarser time scales such as month or year. It produces a valuable platform for adaptation of the model to new crops or for the improvement of the existing parameters set. On daily time scale, validation for highly dynamic variables such as soil water transport remains challenging. • Model application is demonstrated with relevance for scientists and regional managers. The integrated modelling strategy is applicable for other process-based models similar to Daisy. It is envisaged that the strategy establishes model capability as a useful research/decision-making, and it increases knowledge transferability, reproducibility and traceability

An integrated natural remanent magnetization acquisition model for the Matuyama-Brunhes reversal recorded by the Chinese loess

Geomagnetic polarity reversal boundaries are key isochronous chronological controls for the long Chinese loess sequences, and further facilitate paleoclimatic correlation between Chinese loess and marine sediments. However, owing to complexity of postdepositional remanent magnetization (pDRM) acquisition processes related to variable dust sedimentary environments on the Chinese Loess Plateau (CLP), there is a long-standing dispute concerning the downward shift of the pDRM recorded in Chinese loess. In this study, after careful stratigraphic correlation of representative climatic tie points and the Matuyama-Brunhes boundaries (MBB) in the Xifeng, Luochuan, and Mangshan loess sections with different pedogenic environments, the downward shift of the pDRM is semiquantitatively estimated and the acquisition model for the loess natural remanent magnetization (NRM) is discussed. The measured MB transition zone has been affected by the surficial mixing layer (SML) and remagnetization. Paleoprecipitation is suggested to be the dominant factor controlling the pDRM acquisition processes. Rainfall-controlled leaching would restrict the efficiency of the characterized remanent magnetization carriers aligning along the ancient geomagnetic field. We conclude that the MBB in the central CLP with moderate paleoprecipitation could be considered as an isochronous chronological control after moderate upward adjustment. A convincing case can then be made to correlate L8/S8 to MIS 18/1

Feasibility study of biomass gasification integrated with reheating furnaces in steelmaking process

This paper investigates the integration of biosyngas production, reheating furnace and heat recovery steam cycle, in order to use biosyngas directly as fuel in the furnace. A system model was developed to evaluate the feasibility of the proposed system from the perspective of heat and mass balance. To particularly study the impacts of fuel switching on the heating quality of the furnace, a three-dimensional furnace model considering detailed heat transfer processes was embedded into the system through an Aspen PlusTM user defined model. The simulation results show that biosyngas is suitable for direct use as fuel for reheating furnaces. Should CO capture be considered in the proposed system, it has a potential to achieve the capture without external energy input which results in so-called negative emissions of CO

Anomalous Dome-like Superconductivity in RE2(Cu1-xNix)5As3O2(RE=La, Pr, Nd)

Significant manifestation of interplay of superconductivity and charge density wave, spin density wave or magnetism is dome-like variation in superconducting critical temperature (Tc) for cuprate, iron-based and heavy Fermion superconductors. Overall behavior is that the ordered temperature is gradually suppressed and the Tc is enhanced under external control parameters. Many phenomena like pesudogap, quantum critical point and strange metal emerge in the different doping range. Exploring dome-shaped Tc in new superconductors is of importance to detect emergent effects. Here, we report that the observation of superconductivity in new layered Cu-based compound RE2Cu5As3O2 (RE=La, Pr, Nd), in which the Tc exhibits dome-like variation with maximum Tc of 2.5 K, 1.2 K and 1.0 K as substituting Cu by large amount of Ni ions. The transitions of T* in former two compounds can be suppressed by either Ni doping or rare earth replacement. Simultaneously, the structural parameters like As-As bond length and c/a ratio exhibit unusual variations as Ni-doping level goes through the optimal value. The robustness of superconductivity, up to 60% of Ni doping, reveals the unexpected impurity effect on inducing and enhancing superconductivity in this novel layered materialsComment: 16 pages, 5 figures. Comments are welcom