Exploring the Adequacy of Steady-State-Only Calibration

This paper explores the adequacy of steady-state-only calibration as a precursor to use of a groundwater model for decision-support. First, it reviews metrics by which a decision-support model should be judged. On the basis of these metrics, it establishes the shortcomings that a decision-support model may incur through foregoing transient calibration. These are 1) failure to reduce the uncertainties of management-salient model predictions to the extent that available data allows, and 2) creation of unquantifiable bias in management-salient predictions. Two methodologies for quantification of these deficiencies are proposed. The first of these addresses uncertainty reduction. This is relatively easy to implement, as it requires only that sensitivities of pertinent model outputs to a model’s parameters be calculated. The second methodology addresses predictive bias. Implementation of this second methodology is more expensive as it requires repeated calibration of a steady state model against stochastic realizations of a transient model.These methods are demonstrated using a synthetic case which explores the viability of steady-state-only calibration of models deployed to examine the impacts of pumping on stream flows and groundwater levels. It is demonstrated that, for some predictions of management interest, steady-state-only calibration is more than sufficient for this kind of decision-support modelling.

Impacts of initialisation of coupled ice sheet-ocean models forecasting.

<p>In recent years, there have been great advances in coupled ice sheet-ocean modelling, to the point where ice-ocean interactions can be represented in global climate models — with potential to greatly improve forecasting of marine ice-sheet loss and sea level rise in the coming century and beyond. However, initialisation of coupled ice sheet-ocean models has not yet been properly examined; and initialisation approaches applied to ocean and coupled atmosphere-ocean models may not be appropriate due to the long time scales inherent in dynamic ice sheets. Moreover, as ocean melt rates and ice-shelf geometry strongly influence each other, nonphysical transients in incorrectly initialised coupled ice-ocean models may persist for longer than in ice-sheet models alone.</p><p>In this work, two approaches to coupled initialisation are considered using a synchronously coupled ice-ocean model. The two approaches are based on two commonly used approaches to ice sheet model initialisation: “snapshot” calibration, where ice-sheet basal and internal parameters are configured to optimise fit with observed surface velocity; and “transient” calibration, where these parameters are configured to jointly optimise fit with velocity and geometry change; however, the transient calibration makes use of the ocean component to ensure the ice model is not subject to “initialisation shock” from ocean melting. The approaches are applied to Smith Glacier, a small but fast-thinning glacier in West Antarctica, and the model is forced under ocean warming scenarios in multidecadal runs. Initially there is much faster retreat seen in the Snapshot-calibrated simulation, but this difference decays over several decades, and ultimately the Transiently-calibrated model sees more retreat.</p><p>The experiments further suggest that Smith Glacier is not likely to exhibit Marine Ice Sheet instability in the next century. But the methods discrepancy has strong implications for glaciers which are susceptible to this instability.</p>

Intelligent transient calibration of a dual-loop EGR diesel engine using chaos-enhanced accelerated particle swarm optimization algorithm

This article proposes an intelligent transient calibration method for the air-path controller of a light-duty diesel engine. This method is developed based on the chaos-enhanced accelerated particle swarm optimization algorithm. The target is to reduce the engine’s fuel consumption during transient scenarios by optimizing the controller parameters. The advanced dual-loop exhaust gas recirculation system is first introduced. Then, it formulates the transient calibration process as a multiple-objective optimization problem with constraints. Different from steady state calibration, the proposed method designs a new cost-function to evaluate the controller’s transient performance. The intelligent transient calibration module is programmed in MATLAB code. Interface between the calibration module and a physical engine plant is established via ETAS INCA. The optimization result of the proposal method is discussed by comparing it with the result of existing calibration methods. The engine performance with the calibrated controller is evaluated based on engine tests.

Calibrated sub-micron temperature mapping of an operating plasmonic HAMR device by thermoreflectance imaging

ABSTRACTThermal characterization of nano-featured devices is a critical challenge for the development of high performance devices. Although far-field thermoreflectance imaging is limited in spatial resolution by the optical diffraction limit, it is more amenable to absolute temperature calibration of plasmonic devices than existing near-field scanning probe tip methods. We have built an advanced thermoreflectance microscope capable of 50 ns time-resolved, diffraction-limited temperature imaging that can account and correct for thermal expansion, sample drift, numerical aperture, and polarization induced variations in the apparent thermoreflectance coefficient of nanoscale structures. We developed a per-pixel transient calibration technique using this microscope to measure the absolute temperature of an operating heat-assisted magnetic recording (HAMR) head, including features as narrow as 200 nm. The resulting temperature information can be used to experimentally validate numerical models in the design process of such plasmonic devices.

Committed retreat of Smith, Pope, and Kohler Glaciers over the next 30 years inferred by transient model calibration

A glacial flow model of Smith, Pope and Kohler Glaciers is calibrated by means of control methods against time varying, annually resolved observations of ice height and velocities, covering the period 2002 to 2011. The inversion – termed "transient calibration" – produces an optimal set of time-mean, spatially varying parameters together with a time-evolving state that accounts for the transient nature of observations and the model dynamics. Serving as an optimal initial condition, the estimated state for 2011 is used, with no additional forcing, for predicting grounded ice volume loss and grounding line retreat over the ensuing 30 years. The transiently calibrated model predicts a near-steady loss of grounded ice volume of approximately 21 km3 a−1 over this period, as well as loss of 33 km2 a−1 grounded area. We contrast this prediction with one obtained following a commonly used "snapshot" or steady-state inversion, which does not consider time dependence and assumes all observations to be contemporaneous. Transient calibration is shown to achieve a better fit with observations of thinning and grounding line retreat histories, and yields a quantitatively different projection with respect to ice volume loss and ungrounding. Sensitivity studies suggest large near-future levels of unforced, i.e., committed sea level contribution from these ice streams under reasonable assumptions regarding uncertainties of the unknown parameters.

Committed near-future retreat of Smith, Pope, and Kohler Glaciers inferred by transient model calibration

A glacial flow model of Smith, Pope and Kohler Glaciers has been calibrated by means of inverse methods against time-varying, annualy resolved observations of ice height and velocities, covering the period 2002 to 2011. The inversion – termed "transient calibration" – produces an optimal set of time-mean, spatially varying parameters together with a time-evolving state that accounts for the transient nature of observations and the model dynamics. Serving as an optimal initial condition, the estimated state for 2011 is used, with no additional forcing, for predicting grounded ice volume loss and grounding line retreat over the ensuing 30 years. The transiently calibrated model predicts a near-steady loss of grounded ice volume of approximately 21 km3 a−1 over this period, as well as loss of 33 km2 a−1 grounded area. We contrast this prediction with one obtained following a commonly used "snapshot" or steady-state inversion, which does not consider time dependence and assumes all observations to be contemporaneous. Transient calibration is shown to achieve a better fit with observations of thinning and grounding line retreat histories, and yields a quantitatively different projection with respect to ice volume loss and ungrounding. Sensitivity studies suggest large near-future levels of unforced, i.e. committed sea level contribution from these ice streams under reasonable assumptions regarding uncertainties of the unknown parameters.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (Δ P) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine Δ P frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine Δ P must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine Δ P and low fresh air flowrates, while the second mode is driven by high engine Δ P and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.