Inverse Polynomial Based Explicit Guidance for Lunar Soft Landing During Powered Braking

In this paper an explicit guidance law for the powered descent phase of the soft lunar landing is presented. The descent trajectory, expressed in polynomial form is fixed based on the boundary conditions imposed by the precise soft landing mission. Adapting an inverse model based approach, the guidance command is computed from the known spacecraft trajectory. The guidance formulation ensures the vertical orientation of the spacecraft during touchdown. Also a closed form relation for the final flight time is proposed. The final time is expressed as a function of initial position and velocity of the spacecraft ( at the start of descent) and also depends on the desired landing site. To ensure the fuel minimum descent the proposed explicit method is extended to optimal guidance formulation. The effectiveness of the proposed guidance laws are demonstrated with simulation results.

A Numerical Model of Rapid Solidification Processing of Ni-Al Alloy in Planar Flow Casting

A numerical model has been developed for simulating the rapid solidification processing (RSP) of Ni-Al alloy in order to predict the resultant phase composition semi-quantitatively during RSP. The present model couples the initial nucleation temperature evaluating method based on the time dependent nucleation theory, and solidified volume fraction calculation model based on the kinetics model of dendrite growth in undercooled melt. This model has been applied to predict the cooling curve and the volume fraction of solidified phases of Ni-Al alloy in planar flow casting. The numerical results agree with the experimental results semi-quantitatively.

A second-order dynamic subgrid-scale stress model

A second-order dynamic model based on the general relation between the subgrid-scale stress and the velocity gradient tensors was proposed. A priori test of the second-order model was made using moderate resolution direct numerical simulation date at high Reynolds number ( Taylor microscale Reynolds number R-lambda = 102 similar to 216) for homogeneous, isotropic forced flow, decaying flow, and homogeneous rotating flow. Numerical testing shows that the second-order dynamic model significantly improves the correlation coefficient when compared to the first-order dynamic models.

Cyclical Features of Uzawa-Lucas Endogenous Growth Model

This paper analyzes the cyclical properties of a generalized version of Uzawa-Lucas endogenous growth model. We study the dynamic features of different cyclical components of this model characterized by a variety of decomposition methods. The decomposition methods considered can be classified in two groups. On the one hand, we consider three statistical filters: the Hodrick-Prescott filter, the Baxter-King filter and Gonzalo-Granger decomposition. On the other hand, we use four model-based decomposition methods. The latter decomposition procedures share the property that the cyclical components obtained by these methods preserve the log-linear approximation of the Euler-equation restrictions imposed by the agent’s intertemporal optimization problem. The paper shows that both model dynamics and model performance substantially vary across decomposition methods. A parallel exercise is carried out with a standard real business cycle model. The results should help researchers to better understand the performance of Uzawa-Lucas model in relation to standard business cycle models under alternative definitions of the business cycle.

A model of the olfactory bulb and beyond

The olfactory bulb of mammals aids in the discrimination of odors. A mathematical model based on the bulbar anatomy and electrophysiology is described. Simulations of the highly non-linear model produce a 35-60 Hz modulated activity, which is coherent across the bulb. The decision states (for the odor information) in this system can be thought of as stable cycles, rather than as point stable states typical of simpler neuro-computing models. Analysis shows that a group of coupled non-linear oscillators are responsible for the oscillatory activities. The output oscillation pattern of the bulb is determined by the odor input. The model provides a framework in which to understand the transformation between odor input and bulbar output to the olfactory cortex. This model can also be extended to other brain areas such as the hippocampus, thalamus, and neocortex, which show oscillatory neural activities. There is significant correspondence between the model behavior and observed electrophysiology.

It has also been suggested that the olfactory bulb, the first processing center after the sensory cells in the olfactory pathway, plays a role in olfactory adaptation, odor sensitivity enhancement by motivation, and other olfactory psychophysical phenomena. The input from the higher olfactory centers to the inhibitory cells in the bulb are shown to be able to modulate the response, and thus the sensitivity, of the bulb to odor input. It follows that the bulb can decrease its sensitivity to a pre-existing and detected odor (adaptation) while remaining sensitive to new odors, or can increase its sensitivity to discover interesting new odors. Other olfactory psychophysical phenomena such as cross-adaptation are also discussed.

A Unifying model of strategic network formation

Documento de trabajo

Active reservoir management: a model solution

Steady-state procedures, of their very nature, cannot deal with dynamic situations. Statistical models require extensive calibration, and predictions often have to be made for environmental conditions which are often outside the original calibration conditions. In addition, the calibration requirement makes them difficult to transfer to other lakes. To date, no computer programs have been developed which will successfully predict changes in species of algae. The obvious solution to these limitations is to apply our limnological knowledge to the problem and develop functional models, so reducing the requirement for such rigorous calibration. Reynolds has proposed a model, based on fundamental principles of algal response to environmental events, which has successfully recreated the maximum observed biomass, the timing of events and a fair simulation of the species succession in several lakes. A forerunner of this model was developed jointly with Welsh Water under contract to Messrs. Wallace Evans and Partners, for use in the Cardiff Bay Barrage study. In this paper the authors test a much developed form of this original model against a more complex data-set and, using a simple example, show how it can be applied as an aid in the choice of management strategy for the reduction of problems caused by eutrophication. Some further developments of the model are indicated.

A catch-free stock assessment model with application to goliath grouper (Epinephelus itajara) off southern Florida

Many modern stock assessment methods provide the machinery for determining the status of a stock in relation to certain reference points and for estimating how quickly a stock can be rebuilt. However, these methods typically require catch data, which are not always available. We introduce a model-based framework for estimating reference points, stock status, and recovery times in situations where catch data and other measures of absolute abundance are unavailable. The specif ic estimator developed is essentially an age-structured production model recast in terms relative to pre-exploitation levels. A Bayesian estimation scheme is adopted to allow the incorporation of pertinent auxiliary information such as might be obtained from meta-analyses of similar stocks or anecdotal observations. The approach is applied to the population of goliath grouper (Epinephelus itajara) off southern Florida, for which there are three indices of relative abundance but no reliable catch data. The results confirm anecdotal accounts of a marked decline in abundance during the 1980s followed by a substantial increase after the harvest of goliath grouper was banned in 1990. The ban appears to have reduced fishing pressure to between 10% and 50% of the levels observed during the 1980s. Nevertheless, the predicted fishing mortality rate under the ban appears to remain substantial, perhaps owing to illegal harvest and depth-related release mortality. As a result, the base model predicts that there is less than a 40% chance that the spawning biomass will recover to a level that would produce a 50% spawning potential ratio.

A simulation model of the dynamics of Peruvian anchoveta (Engraulis ringens)

The article describes the key elements of a model simulating the dynamics of the anchoveta (Engraulis ringens) in the Peruvian upwelling system (4 degrees to 14 degrees South). This model, based on coupled differential equations, is parametrized mainly using empirical data and functional relationships presented in two volumes issued by ICLARM in 1987 and 1989, and may thus be viewed as test of the hypotheses presented therein. Results to date suggest that present knowledge of mechanisms controlling the anchoveta stock is essentially consistent, and sufficient to build a model reflecting essential features of the stock biomass and recruitment dynamics.

Application of a wind-driven barotropic model to simulate the seasonal circulation of the northern Arabian Sea

A two dimensional numerical barotropic model based on the depth-integrated equations is presented here. Sensitivity of the model is analyzed by using wind stresses of different months. Real wind data and actual bathymetry are used as an input to obtain the circulation patterns of the northern Arabian Sea during specific seasons. However, the model is also tested with constant depth for comparison. A number of numerical simulations are performed to study the combined effects of wind stress, bathymetry and basin geometry. Since the goal of this study is to simulate the circulation of the northern Arabian sea in accordance with the observed wind stress, therefore, wind stresses of different months like July (the peak os SW monsoon), October (the transition period from SW to NE monsoon), January (the peack of NE monsoon) and April (the transition period from NE to SW monsoon) are used to examine the circulation patterns. The results obtained are satisfactory in that they resemble known patterns.

A procedure for automatically estimating model parameters in optical motion capture

Model-based optical motion capture systems require knowledge of the position of the markers relative to the underlying skeleton, the lengths of the skeleton's limbs, and which limb each marker is attached to. These model parameters are typically assumed and entered into the system manually, although techniques exist for calculating some of them, such as the position of the markers relative to the skeleton's joints. We present a fully automatic procedure for determining these model parameters. It tracks the 2D positions of the markers on the cameras' image planes and determines which markers lie on each limb before calculating the position of the underlying skeleton. The only assumption is that the skeleton consists of rigid limbs connected with ball joints. The proposed system is demonstrated on a number of real data examples and is shown to calculate good estimates of the model parameters in each. © 2004 Elsevier B.V. All rights reserved.

Modeling and electrical measurement of transport AC loss in HTS-based superconducting coils for electric machines

AC loss can be a significant problem for any applications that utilize or produce an AC current or magnetic field, such as an electric machine. The authors are currently investigating the electromagnetic properties of high temperature superconductors with a particular focus on the AC loss in coils made from YBCO superconductors. In this paper, a 2D finite element model based on the H formulation is introduced. The model is then used to calculate the transport AC loss using both a bulk approximation and modeling the individual turns in a racetrack-shaped coil. The coil model is based on the superconducting stator coils used in the University of Cambridge EPEC Superconductivity Group's superconducting permanent magnet synchronous motor design. The transport AC loss of a stator coil is measured using an electrical method based on inductive compensation using a variable mutual inductance. The simulated results are compared with the experimental results, verifying the validity of the model, and ways to improve the accuracy of the model are discussed. © 2010 IEEE.

Factor analysis based VTS and JUD noise estimation and compensation

Model based compensation schemes are a powerful approach for noise robust speech recognition. Recently there have been a number of investigations into adaptive training, and estimating the noise models used for model adaptation. This paper examines the use of EM-based schemes for both canonical models and noise estimation, including discriminative adaptive training. One issue that arises when estimating the noise model is a mismatch between the noise estimation approximation and final model compensation scheme. This paper proposes FA-style compensation where this mismatch is eliminated, though at the expense of a sensitivity to the initial noise estimates. EM-based discriminative adaptive training is evaluated on in-car and Aurora4 tasks. FA-style compensation is then evaluated in an incremental mode on the in-car task. © 2011 IEEE.

Industrial ecology at factory level - A conceptual model

Growing environmental concerns caused by natural resource depletion and pollution need to be addressed. One approach to these problems is Sustainable Development, a key concept for our society to meet present as well as future needs worldwide. Manufacturing clearly has a major role to play in the move towards a more sustainable society. However it appears that basic principles of environmental sustainability are not systematically applied, with practice tending to focus on local improvements. The aim of the work presented in this paper is to adopt a more holistic view of the factory unit to enable opportunities for wider improvement. This research analyses environmental principles and industrial practice to develop a conceptual manufacturing ecosystem model as a foundation to improve environmental performance. The model developed focuses on material, energy and waste flows to better understand the interactions between manufacturing operations, supporting facilities and surrounding buildings. The research was conducted in three steps: (1) existing concepts and models for industrial sustainability were reviewed and environmental practices in manufacturing were collected and analysed; (2) gaps in knowledge and practice were identified; (3) the outcome is a manufacturing ecosystem model based on industrial ecology (IE). This conceptual model has novelty in detailing IE application at factory level and integrating all resource flows. The work is a base on which to build quantitative modelling tools to seek integrated solutions for lower resource input, higher resource productivity, fewer wastes and emissions, and lower operating cost within the boundary of a factory unit. © 2012 Elsevier Ltd. All rights reserved.