Accurate Empirical Model Research Articles

A single-site multipole model for liquid water.

Accurate and efficient empirical potential energy models that describe the atomistic interactions between water molecules in the liquid phase are essential for computer simulations of many problems in physics, chemistry, and biology, especially when long length or time scales are important. However, while models with non-polarizable partial charges at four or five sites in a water molecule give remarkably good values for certain properties, deficiencies have been noted in other properties and increasing the number of sites decreases computational efficiency. An alternate approach is to utilize a multipole expansion of the electrostatic potential due to the molecular charge distribution, which is exact outside the charge distribution in the limits of infinite distances or infinite orders of multipoles while partial charges are a qualitative representation of electron density as point charges. Here, a single-site multipole model of water is presented, which is as fast computationally as three-site models but is also more accurate than four- and five-site models. The dipole, quadrupole, and octupole moments are from quantum mechanical-molecular mechanical calculations so that they account for the average polarization in the liquid phase, and represent both the in-plane and out-of-plane electrostatic potentials of a water molecule in the liquid phase. This model gives accurate thermodynamic, dynamic, and dielectric properties at 298 K and 1 atm, as well as good temperature and pressure dependence of these properties.

Machine learning strategies for systems with invariance properties

In many scientific fields, empirical models are employed to facilitate computational simulations of engineering systems. For example, in fluid mechanics, empirical Reynolds stress closures enable computationally-efficient Reynolds Averaged Navier Stokes simulations. Likewise, in solid mechanics, constitutive relations between the stress and strain in a material are required in deformation analysis. Traditional methods for developing and tuning empirical models usually combine physical intuition with simple regression techniques on limited data sets. The rise of high performance computing has led to a growing availability of high fidelity simulation data. These data open up the possibility of using machine learning algorithms, such as random forests or neural networks, to develop more accurate and general empirical models. A key question when using data-driven algorithms to develop these empirical models is how domain knowledge should be incorporated into the machine learning process. This paper will specifically address physical systems that possess symmetry or invariance properties. Two different methods for teaching a machine learning model an invariance property are compared. In the first method, a basis of invariant inputs is constructed, and the machine learning model is trained upon this basis, thereby embedding the invariance into the model. In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation. Results are discussed for two case studies: one in turbulence modeling and one in crystal elasticity. It is shown that in both cases embedding the invariance property into the input features yields higher performance at significantly reduced computational training costs.

An Accurate Empirical Model Based on Volterra Series for FET Power Detectors

An empirical model for field-effect transistor (FET) based power detectors is presented. The electrical model constitutes a Volterra analysis based on a Taylor series expansion of the drain current together with a linear embedding small-signal circuit. It is fully extracted from S-parameters and IV curves. The final result are closed-form expressions for the frequency dependence of the noise equivalent power (NEP) in terms of the FET intrinsic capacitances and parasitic resistances. Excellent model agreement to measured NEP of coplanar access graphene FETs with varying channel dimensions up to 67 GHz is obtained. The influence of gate length on responsivity and NEP is theoretically and experimentally studied.

On the Use of X-Band Weather Radar for Wind Field Retrieval in Coastal Zone

AbstractThis paper documents the study of the radar signature of the sea surface on the images collected by an X-band weather radar and its application to remote sensing of the coastal zone. The main radar parameters considered here are the reflectivity factor [which was converted into a normalized radar cross section (NRCS)], the differential reflectivity, and the mean radial velocity. Measurements of the NRCS in the vicinity of an instrumented offshore buoy allowed for identifying its variations with wind speed and relative direction, which are found to be consistent with the Georgia Institute of Technology (GIT) model and other measurements. A more accurate empirical model for the NRCS is developed. For moderate to strong winds, the mean radial velocity is linearly related to the radial component of the wind speed, showing the potentiality of weather radars to map the radial surface wind speed at the scale of a basin. The influence of surface currents is weak here but should be likely taken into account in other places with stronger currents. Measurements of the differential reflectivity are also consistent with other measurements made elsewhere for the polarization ratio. The analysis of radar data over the entire coverage could also be performed using surface wind estimates from a meteorological model. Similar but less accurate results are obtained for the NRCS and the mean radial velocity. The extra spatial variability not due to wind speed variations is identified. An inversion procedure is proposed to recover the wind vector field from radar measurements after calibration of the NRCS values. Results are promising and pave the way to the concept of weather radar for ocean remote sensing.

Take-Off and Landing Using Ground-Based Power-Simulation of Critical Landing Load Cases Using Multibody Dynamics

AbstractA novel take-off and landing system using ground-based power is proposed in the EU-FP7 project GABRIEL. The main feature of this system is the complete removal of the landing gear from civil aircraft. The proposed system has the potential to reduce aircraft weight, emissions, and noise. A feasibility study of the structural design of the connection mechanism between aircraft and ground system has been performed by simulating the landing procedure on a moving ground system. One of the key challenges is the landing on a moving ground system under high crosswind conditions. The main focus in the current research is the calculation of the critical dynamic loads on both aircraft and ground system for a wide range of landing conditions (sink rate, velocity differences between aircraft and ground system, etc.). For comparison, conventional landing procedures with a traditional landing (TL) gear have also been simulated. The aerodynamics of the aircraft is represented by an accurate empirical model. The r...

A combined model for the solubility of different compounds in supercritical carbon dioxide

The solubility is one of the most important physicochemical characteristics of chemical process. Correlations and predictive techniques are currently being developed to generate solubility data. The empirical correlations are quite successful in correlating the solubility of compounds in the supercritical fluids. In this work, a combined model, based on the optimization theory, was proposed to correlate different compounds in supercritical carbon dioxide. Solubility data from 48 different compounds were collected from literature published from the year of 2008–2013. The global average absolute relative deviations (AARD) of the model results from 1116 experimental data points were reported to investigate the capability of the proposed model and the mostly more accurate empirical models (Ch–Madras, Garlapati–Madras, Adachi–Lu, Jouyban, Sparks, and Bian) in calculations of the solubilities. The results showed that, the proposed Sparks–Jouyban–Bian combined model produced more accurate results (AARD=4.37%) compared to the six most common empirical models and seven other combined models considered in this study.

GTm-III: a new global empirical model for mapping zenith wet delays onto precipitable water vapour

SUMMARY The weighted mean temperature (Tm) is a critical parameter in research of GPS meteorology. Recently, we have established two global Tm models, GTm-I and GTm-�, using groundbased radiosonde data. These two models, which directly use the location and the day of year to calculate Tm, consider the annual cycle only. In this study, we further take into account the variation characteristics of Tm in semi-annual and diurnal periodicity and estimate the initial phase of each cycle. A more accurate global empirical Tm model called GTm-III is constructed using high-precision Global Geodetic Observing System (GGOS) AtmosphereTm grid data, and then validated using a new set ofTm grid data, radiosonde data and Constellation Observation System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation data. Results indicate that compared to the existing global Tm models, GTm-III provides Tm estimates of high accuracy on a global scale and the predicted values are close to the true values in every moment of every day.

Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts

Our current understanding of how DNA is packed in the nucleus is most accurate at the fine scale of individual nucleosomes and at the large scale of chromosome territories. However, accurate modeling of DNA architecture at the intermediate scale of ∼50 kb–10 Mb is crucial for identifying functional interactions among regulatory elements and their target promoters. We describe a method, Fit-Hi-C, that assigns statistical confidence estimates to mid-range intra-chromosomal contacts by jointly modeling the random polymer looping effect and previously observed technical biases in Hi-C data sets. We demonstrate that our proposed approach computes accurate empirical null models of contact probability without any distribution assumption, corrects for binning artifacts, and provides improved statistical power relative to a previously described method. High-confidence contacts identified by Fit-Hi-C preferentially link expressed gene promoters to active enhancers identified by chromatin signatures in human embryonic stem cells (ESCs), capture 77% of RNA polymerase II-mediated enhancer-promoter interactions identified using ChIA-PET in mouse ESCs, and confirm previously validated, cell line-specific interactions in mouse cortex cells. We observe that insulators and heterochromatin regions are hubs for high-confidence contacts, while promoters and strong enhancers are involved in fewer contacts. We also observe that binding peaks of master pluripotency factors such as NANOG and POU5F1 are highly enriched in high-confidence contacts for human ESCs. Furthermore, we show that pairs of loci linked by high-confidence contacts exhibit similar replication timing in human and mouse ESCs and preferentially lie within the boundaries of topological domains for human and mouse cell lines.

Empirical model of total internal reflection from highly turbid media

We demonstrate, to the best of our knowledge, a first accurate empirical model for reflectance measurements from highly turbid media over the full range of incident angles, i.e., for reflectivity values going from unity in the total internal reflection regime to nearly zero when almost all the light is transmitted. Evidence that our model is accurate is provided by extraction of the particle size, followed by independent verification with dynamic light scattering. Our methodology is in direct contrast with the prevalent approach in turbid media of focusing on only the critical angle region, which is just a small subset of the entire reflectance data.

Performance analysis of small capacity absorption chillers by using different modeling methods

This paper presents a review and comparison of simple, yet accurate steady-state models of small capacity absorption chillers using highly reliable experimental data obtained with an absorption chiller of 12 kW in a state-of-the-art test bench. These models can potentially be used in complete modeling and simulation tools or in supervisory control strategies for air-conditioning systems using absorption chillers.With respect to that, a comparative evaluation of different modeling methods for predicting the absorption chiller performance is presented. Four empirically based models: the adapted Gordon-Ng model (GNA), the characteristic equation model (ΔΔt′), the multivariable polynomial model (MPR) and the artificial neural networks model (ANN) were applied using the experimental data and thoroughly examined. The paper also presents statistical indicators and tests which might assist in selection of the most appropriate model.The excellent statistical indicators such as coefficient of determination (>0.99) and coefficient of variation (<5%) clearly indicate that it is possible to develop highly accurate empirical models by using only the variables of external water circuits as model input parameters.

Control of pneumatic artificial muscle system through experimental modelling

This paper deals with position control of a single degree of freedom (sdof) manipulator actuated by Pneumatic Artificial Muscle (PAM) actuator. Though the compliance characteristics of these actuators are desirable, their inherent non-linearities due to compressibility of air and non-linear load–contraction characteristics make them difficult to model and design of controller becomes very complex. To overcome this, a novel method is hereby proposed to establish an accurate empirical model for the system. The quasi-static characteristics of the PAM are first modelled followed by the dynamic characteristics through spectral analysis. For cost competitiveness, the present work incorporates inexpensive on–off switching valves operated using a novel model based proportional pressure regulator developed using a modified PWM algorithm. Finally, a conventional PID position controller is extended using the empirical PAM model and an inner pressure regulation loop to achieve trajectory tracking of a sdof manipulator. Results for pressure regulation and position control confirm the effectiveness of the adopted approach in achieving performance comparable to the state-of-the-art results at a reduced control complexity and total set-up cost.

Nonequilibrium molecular dynamics simulations of the thermal conductivity of water: A systematic investigation of the SPC/E and TIP4P/2005 models

We report an extensive nonequilibrium molecular dynamics investigation of the thermal conductivity of water using two of the most accurate rigid nonpolarizable empirical models available, SPC/E and TIP4P/2005. Our study covers liquid and supercritical states. Both models predict the anomalous increase of the thermal conductivity with temperature and the thermal conductivity maximum, hence confirming their ability to reproduce the complex anomalous behaviour of water. The performance of the models strongly depends on the thermodynamic state investigated, and best agreement with experiment is obtained for states close to the liquid coexistence line and at high densities and temperatures. Considering the simplicity of these two models the overall agreement with experiments is remarkable. Our results show that explicit polarizability and molecular flexibility are not needed to reproduce the anomalous heat conduction of water.

Empirical valence bond models for reactive potential energy surfaces: A parallel multilevel genetic program approach

We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent.

Modelling of a thermomechanically coupled forming process based on functional outputs from a finite element analysis and from experimental measurements

In this paper, measurements from experiments and results of a finite element analysis (FEA) are combined in order to compute accurate empirical models for the temperature distribution before a thermomechanically coupled forming process. To accomplish this, Design and Analysis of Computer Experiments (DACE) is used to separately compute models for the measurements and the functional output of the FEA. Based on a hierarchical approach, a combined model of the process is computed. In this combined modelling approach, the model for the FEA is corrected by taking into account the systematic deviations from the experimental measurements. The large number of observations based on the functional output hinders the direct computation of the DACE models due to the internal inversion of the correlation matrix. Thus, different techniques for identifying a relevant subset of the observations are proposed. The application of the resulting procedure is presented, and a statistical validation of the empirical models is performed.

A compact and accurate empirical model for turbine mass flow characteristics

The model of turbine mass flow characteristics is vital to simulate equipment and systems having a turbine, such as renewable energy power systems, air cycle refrigeration systems, power plants, and turbine engines. Existing empirical and partly empirical models of turbine mass flow characteristics need to be improved either to increase the prediction accuracy and extrapolation performance or to reduce complexity. A new empirical model describing the turbine mass flow performance map, also called a mean value model, is developed through extensive computing tests using curve fitting and nonlinear regression software. Measured data of a turbocharger turbine and a simple air cycle machine (ACM) turbine are used for the model building. The proposed model is highly compact and accurate, its predictions agree with measured data very well, and it has excellent extrapolation performances as well. The mean absolute relative error is 1.38% for the simple ACM turbine and 0.91% for the turbocharger turbine. Comparison with the best existing model shows that the new model reduces the mean absolute relative error by about 40%, and is much easier to use and much more compact.

Precise size control of inkjet-printed droplets on a flexible polymer substrate using plasma surface treatment

The effect of plasma surface treatment on the dried diameter of droplets inkjet-printed on the PI substrate was investigated by varying the plasma process parameters. The sequential design of the experiments technique combining a factorial design with a response surface method was introduced to systematically estimate an accurate empirical response model for two independent design variables: radio frequency (RF) power and gas pressure. C4F8 gas was used for the plasma surface treatment of 90 mm × 90 mm polyimide substrates. Ag ink droplets ejected from a 30 µm nozzle were printed on the plasma-treated substrates, and their measured diameter and standard deviation were used as the response variables. The plasma-treated substrate was also characterized by contact angles and x-ray photoelectron spectroscopy. The results indicate that the droplet diameters and their uniformity are sensitive to changes in both RF power and gas pressure, lower droplet diameters on PI substrates correspond to lower surface energies, and the process condition producing higher F content results in more hydrophobic surface. The resolution of the inkjet printing can be precisely controlled by varying the droplet diameter and uniformity through the C4F8 plasma surface treatment.

Design and performance of metal conductors for stretchable electronic circuits

PurposeThe purpose of this paper is to present an update on the progress of the design and reliability of stretchable interconnections for electronic circuits.Design/methodology/approachFinite element modelling (FEM) is used to analyse the physical behaviour of stretchable interconnects under different loading conditions. The fatigue life of a copper interconnect embedded into a silicone matrix has been evaluated using the Coffin‐Manson relation and FEM.FindingsThe mechanical properties of the substrate and the design of the metal interconnection play an important role on the fatigue lifetime of circuit. In the case of copper embedded into a PDMS Sylgard 186, more than 2,500 tensile cycles have been observed for a periodic deformation of 10 per cent.Research limitations/implicationsReliability results are limited and need further work to create a more accurate empirical model to estimate the lifetime of stretchable interconnections.Originality/valueThe combined use of FEM and experimental analysis enable a more reliable design of the stretchable metal interconnections. The proposed horseshoe design offers the benefit of reduced permanent damage during elongation.

A behavioral model development methodology for microwave components and integration in VHDL-AMS

The new generation of system-on-chip (SoC) incorporates digital, analogue, radiofrequency (RF)/microwave and mixed-signal components. Therefore, novel design methodologies must be developed to direct the design of these mixed-technology systems, which will have to include accurate behavioral libraries of devices and processes. Thus, this paper describes a behavioral modeling approach which generates accurate empirical models for RF/microwave devices and that can be easily integrated into a VHDL-AMS simulator. This approach is applied to a microwave tunable phase shifter and it is illustrated by the development of a VHDL-AMS model library for RF/microwave applications.

Fade depth scaling with channel bandwidth

The dependence of small-scale fading on bandwidth is quantified experimentally in the 3.1–10.6 GHz band for indoor channels. The fade depth converges to 4 dB at 1 GHz bandwidth, with little reduction for further increase in bandwidth. A simple yet accurate empirical fade depth model is developed, enabling convenient evaluation of the link budget for a channel with given bandwidth.

Development of methods identifying parameters in reaction wheel assembly disturbance model

PurposeTo set up the analytical model of reaction wheel assembly (RWA) by using the other theory and to provide a new method to identify the parameters of the empirical model of RWA.Design/methodology/approachSetting up the analytical model of RWA using virtual work theory, and presents the energy compensation method. The energy compensation method to improve the computation accuracy of amplitude coefficients of the empirical model of RWA. In the empirical model of RWA, the assumption is that the disturbances consist of discrete harmonics, and the amplitudes is proportion to the square of the wheel speed.FindingsThe errors of amplitude coefficients adopting energy compensation window excel the amplitude spectrum method. The energy compensation method improves the parameters identification accuracy, and provides a new method to set up more accurate empirical disturbance model of RWA.Practical implicationsProviding a valuable identification method of amplitude coefficients of the empirical model of RWA, and improving the accuracy of identification.Originality/valuePutting forward up the method of energy compensation to identify the amplitude coefficients of the empirical model of RWA, and improving the accuracy. This method is simple, practical for the system design.