Unconstrained Simulation Research Articles

Emergent constraints on future extreme precipitation intensification: from global to continental scales

Extreme precipitation intensification due to global warming has received significant attention; however, large uncertainties remain regarding how much it will change in the future, even under a given greenhouse gas emissions pathway. Our constraining analysis provides smaller future extreme precipitation intensification with reduced uncertainties than raw/unconstrained model simulation projections from the global to continental scales and also several sub-continental areas. Historical warming trends in climate model simulations present strong positive inter-model correlations with future annual maximum daily precipitation intensification from the global to continental scales. This emergent relationship is employed for constraining analysis. The proposed emergent constraints are mostly associated with thermodynamics (atmospheric moisture changes), with limited contribution from dynamics (atmospheric circulation variations). This constraining framework has various advantages, including lower observation uncertainty, and more robust theoretical interpretation than previously suggested constraints for extreme precipitation frequency projections. CMIP6 models generally overestimate historically observed warming, which resultantly generates weaker extreme precipitation intensification following constraining analysis than unconstrained model simulation projections from the global to individual continents, and even several mid- and high-latitude sub-continental areas. Additionally, constrained projections exhibit narrower uncertainty ranges in future extreme precipitation projections. During the late 21st century (2070–2099), under the high-emission scenario (Shared Socioeconomic Pathway 5–8.5, characterized by fossil fueled development and a radiative forcing of 8.5 W m−2 in 2100), our results present reduced global average intensity and uncertainty for future annual maximum daily precipitation intensification by 25% and 27%, respectively.

A local universe model for constrained simulations

ABSTRACT The aim of cosmological simulations is to reproduce the properties of the observed Universe, serving as tools to test structure and galaxy formation models. Constrained simulations of our local cosmological region up to a few hundred $h^{-1}\, \mbox{Mpc}$ , the Local Universe, are designed to reproduce the actual cosmic web of structures as observed. A question that often arises is how to judge the quality of constrained simulations against the observations of the Local Universe. Here we introduce the Local Universe model (LUM), a new methodology, whereby many constrained simulations can be judged and the ‘best’ initial conditions can be identified. By characterizing the Local Universe as a set of rich clusters, the model identifies haloes that serve as simulated counterparts to the observed clusters. Their merit is determined against a null hypothesis, the probability that such a counterpart could be identified in a random, unconstrained simulation. This model is applied to 100 constrained simulations using the Cosmicflows-3 data. Cluster counterparts are found for all constrained simulations, their distribution of separation from the true observed cluster position and their mass distribution are investigated. Lastly, the ‘best’ constrained simulation is selected using the LUM and discussed in more detail.

Short range order of glassy KSb5S8 by diffraction, EXAFS, vibrational spectroscopy and DFT calculations

We report on a detailed experimental and simulation study of the short- and medium-range order of a potential phase change material – glassy KSb5S8. On the experimental side, diffraction techniques and EXAFS have been employed to record accurate structural data. Structural models have been generated by fitting multiple datasets simultaneously with the reverse Monte Carlo simulation technique. In addition, density functional theory was employed to study the structure and vibrational modes of selected clusters, representative of the glass structure. Unconstrained RMC simulation runs revealed that the average Sb-S coordination number is 3.18 ± 0.2, thus Sb is mostly threefold coordinated in the glassy state. The fraction of edge and corner sharing SbSn polyhedra and distribution of bridging S atoms (Qn distribution) have also been obtained. Distribution of bridging S atoms around Sb is similar in the crystalline and glassy states. DFT calculations assisted in the identification of a Raman mode at ∼468 cm−1, assigned to hypervalent bonding (quasi-tetrahedral units) in the glass structure.

Character hit reaction animations using physics and inverse kinematics

AbstractCharacter hit reaction is an inherent component in game development. Natural hit reactions in games are typically achieved through the use of artist‐created hit animations and motion capture. To improve the realism of impact reactions, game developers combine physics simulation with distinct hit animations based on character statuses. However, there is currently no method that can automatically produce hit reactions based on hit information in game development. To this end, we propose a physics‐driven inverse kinematic method for generating character reaction animations. We postulate that a character's hit reactions are the result of an assault impulse spreading throughout the body and forcing the body to move. Five IK (inverse kinematics) solvers are used to control character poses. Each IK solver is used to control the movement of a different part of the body. The IK solvers, which are used to determine the positions of various bodily parts, are driven by unconstrained physics simulation. Furthermore, physics simulation with constraints is used to fine‐tune the character's movements. Experiment results show that our method outperforms Unreal Engine‐based hit animation and physics simulation.

Kinetic reconstruction of free energies as a function of multiple order parameters.

A vast array of phenomena, ranging from chemical reactions to phase transformations, are analyzed in terms of a free energy surface defined with respect to a single or multiple order parameters. Enhanced sampling methods are typically used, especially in the presence of large free energy barriers, to estimate free energies using biasing protocols and sampling of transition paths. Kinetic reconstructions of free energy barriers of intermediate height have been performed, with respect to a single order parameter, employing the steady state properties of unconstrained simulation trajectories when barrier crossing is achievable with reasonable computational effort. Considering such cases, we describe a method to estimate free energy surfaces with respect to multiple order parameters from a steady state ensemble of trajectories. The approach applies to cases where the transition rates between pairs of order parameter values considered is not affected by the presence of an absorbing boundary, whereas the macroscopic fluxes and sampling probabilities are. We demonstrate the applicability of our prescription on different test cases of random walkers executing Brownian motion in order parameter space with an underlying (free) energy landscape and discuss strategies to improve numerical estimates of the fluxes and sampling. We next use this approach to reconstruct the free energy surface for supercooled liquid silicon with respect to the degree of crystallinity and density, from unconstrained molecular dynamics simulations, and obtain results quantitatively consistent with earlier results from umbrella sampling.

Resonant Diurnal Internal Tides in the North Atlantic: 2. Modeling

AbstractAn unconstrained global ocean simulation for 2020 supports past observations of diurnal internal tides by acoustic tomography during the 1991–1992 Acoustic Mid‐Ocean Dynamics Experiment in the Western North Atlantic. Explicitly representing the tides, the simulation reproduces the functional form and resonant state of K1 and O1 internal‐tide standing waves, while providing a more realistic physical picture of them. The tomographic data were used to predict the tides in 2020. Not surprisingly, the characteristics of the barotropic and internal tides of the unconstrained simulation deviate from observations. The simulated barotropic tidal currents have excessive, irregular amplitude and lead the acoustic tidal predictions by about 2 hr. While internal‐tide phase coherence is apparent, the simulated internal‐tide variations were irregular in amplitude and phase, unlike the observations. The tomographic tidal measurements therefore provide a quantitative benchmark for improved model representation of tides, internal tides, and dissipation.

Assimilation of Wheat and Soil States into the APSIM-Wheat Crop Model: A Case Study

Optimised farm crop productivity requires careful management in response to the spatial and temporal variability of yield. Accordingly, combination of crop simulation models and remote sensing data provides a pathway for providing the spatially variable information needed on current crop status and the expected yield. An ensemble Kalman filter (EnKF) data assimilation framework was developed to assimilate plant and soil observations into a prediction model to improve crop development and yield forecasting. Specifically, this study explored the performance of assimilating state observations into the APSIM-Wheat model using a dataset collected during the 2018/19 wheat season at a farm near Cora Lynn in Victoria, Australia. The assimilated state variables include (1) ground-based measurements of Leaf Area Index (LAI), soil moisture throughout the profile, biomass, and soil nitrate-nitrogen; and (2) remotely sensed observations of LAI and surface soil moisture. In a baseline scenario, an unconstrained (open-loop) simulation greatly underestimated the wheat grain with a relative difference (RD) of −38.3%, while the assimilation constrained simulations using ground-based LAI, ground-based biomass, and remotely sensed LAI were all found to improve the RD, reducing it to −32.7%, −9.4%, and −7.6%, respectively. Further improvements in yield estimation were found when: (1) wheat states were assimilated in phenological stages 4 and 5 (end of juvenile to flowering), (2) plot-specific remotely sensed LAI was used instead of the field average, and (3) wheat phenology was constrained by ground observations. Even when using parameters that were not accurately calibrated or measured, the assimilation of LAI and biomass still provided improved yield estimation over that from an open-loop simulation.

The Arctic Subpolar Gyre sTate Estimate: Description and Assessment of a Data‐Constrained, Dynamically Consistent Ocean‐Sea Ice Estimate for 2002–2017

AbstractA description and assessment of the first release of the Arctic Subpolar gyre sTate Estimate (ASTE_R1), a data‐constrained ocean‐sea ice model‐data synthesis, is presented. ASTE_R1 has a nominal resolution of 1/3° and spans the period 2002–2017. The fit of the model to an extensive (O(109)) set of satellite and in situ observations was achieved through adjoint‐based nonlinear least squares optimization. The improvement of the solution compared to an unconstrained simulation is reflected in misfit reductions of 77% for Argo, 50% for satellite sea surface height, 58% for the Fram Strait mooring, 65% for Ice Tethered Profilers, and 83% for sea ice extent. Exact dynamical and kinematic consistency is a key advantage of ASTE_R1, distinguishing the state estimate from existing ocean reanalyses. Through strict adherence to conservation laws, all sources and sinks within ASTE_R1 can be accounted for, permitting meaningful analysis of closed budgets at the grid‐scale, such as contributions of horizontal and vertical convergence to the tendencies of heat and salt. ASTE_R1 thus serves as the biggest effort undertaken to date of producing a specialized Arctic ocean‐ice estimate over the 21st century. Transports of volume, heat, and freshwater are consistent with published observation‐based estimates across important Arctic Mediterranean gateways. Interannual variability and low frequency trends of freshwater and heat content are well represented in the Barents Sea, western Arctic halocline, and east subpolar North Atlantic. Systematic biases remain in ASTE_R1, including a warm bias in the Atlantic Water layer in the Arctic and deficient freshwater inputs from rivers and Greenland discharge.

Impact of Prospective Climate Change Scenarios upon Hydropower Potential of Ethiopia in GERD and GIBE Dams

Ethiopia is growing fast, and the country has a dire need of energy. To avoid environmental damages, however, Ethiopia is looking for green energy polices, including hydropower exploitation, with large water availability (i.e., the Blue Nile, the greatest tributary of Nile river). Besides other dams on the Omo river, the GIBE family, Ethiopia is now building the largest hydropower plant of Africa, the GERD (Grand Ethiopian Renaissance Dam), on the Blue Nile river, leading to tensions between Ethiopia, and Egypt, due to potentially conflictive water management. In addition, present and prospective climate change may affect reservoirs’ operation, and this thereby is relevant for downstream water users, population, and environment. Here, we evaluated water management for the GERD, and GIBE III dams, under present, and future hydrological conditions until 2100. We used two models, namely, Poli-Hydro and Poli-Power, to describe (i) hydrological budget, and flow routing and (ii) optimal/maximum hydropower production from the two dams, under unconstrained (i.e., no release downstream besides MIF) and constrained (i.e., with fair release downstream) simulation. We then used climate change scenarios from the reports CMIP5/6 of the Intergovernmental Panel on Climate Change (IPCC) until 2100, to assess future hydropower production. Our results demonstrate that the filling phase of the GERD, particularly critical, have optimal filling time of 5 years or so. Stream flows at GERD could be greater than the present ones (control run CR) at half century (2050–2059), but there could be large decrease at the end of century (2090–2099). Energy production at half century may increase, and then decrease until the end of century. In GIBE III discharges would increase both at half century, and at the end of century, and so would energy production. Constrained, and unconstrained simulation provide in practice similar results, suggesting potential for shared water management in both plants.

Is the Taylor rule optimal? Evaluation using a wavelet-based control model

ABSTRACT This paper extends the wavelet-based control (WBC) model of Crowley and Hudgins (2015) to compare the simulated performance of jointly optimal fiscal and monetary policy, where the policymakers place emphasis on a variety of macroeconomic targets, with the case where monetary policy follows a modified Taylor rule. The results show that the Taylor rule is likely to render higher interest rates, diminished investment, and appreciated real exchange rates compared with an unconstrained baseline simulation. We therefore find that the Taylor rule is suboptimal since it results in higher fiscal deficits due to substitution by policy authorities, thus confirming recent research on the interaction of fiscal and monetary policies. The analysis also compares the baseline and Taylor rule simulated forecasts when the central bank adopts a ‘hawkish’ inflation policy compared to a more ‘dovish’ policy stance.

Mixing state evolution of agglomerating particles in an aerosol chamber: Comparison of measurements and particle-resolved simulations

This article presents a validation study of the stochastic particle-resolved aerosol model PartMC with experimental data from an aerosol chamber experiment. For the experiment, a scanning mobility particle sizer and a single-particle soot photometer were used to monitor the aerosol mixing state evolution of two initially externally mixed aerosol populations of ammonium sulfate and black carbon particles undergoing agglomeration. We applied an efficient optimization algorithm (ProSRS) to determine several unconstrained simulation parameters and were able to successfully reproduce number concentrations and size distributions of mixed particles that formed by agglomeration. The PartMC modeling approach in conjunction with the optimization procedure provides a tool for detailed comparisons of chamber experiments and modeling, where aerosol mixing state is the focus of investigation.Copyright © 2019 American Association for Aerosol Research

Requirements for an Integrated in situ Atlantic Ocean Observing System From Coordinated Observing System Simulation Experiments

A coordinated effort based on Observing System Simulation Experiments (OSSEs) has been carried out for the first time by four European ocean forecasting centers in order to provide insights on the present and future design of the in situ Atlantic Ocean observing system from a monitoring and forecasting perspective. This multi-system approach is based on assimilating synthetic data sets, obtained by sub-sampling in space and time an eddy-resolving unconstrained simulation, named the Nature Run. To assess the ability of a given Atlantic Ocean observing system to constrain the ocean model state, a set of assimilating experiments were performed using four global eddy-permitting systems. For each set of experiments, different designs of the in situ observing system have been assimilated, such as implementing a global drifter array equipped with a thermistor chain down to 150 m depth or extending a part of the global Argo array in the deep ocean. While results from the four systems show similarities and differences, the comparison of the experiments with the Nature Run generally demonstrates a positive impact of the different extra observation networks on the temperature and salinity fields. The spread of the multi-system simulations, combined with the sensitivity of each system to the evaluated observing networks, allowed us to discuss the robustness of the results and their dependence on the specific analysis system. By helping define and test future observing systems from an integrated observing system view, the present work is an initial step toward better-coordinated initiatives for supporting the evolution of the ocean observing system and its integration within ocean monitoring and forecasting systems.

GENERAL-RELATIVISTIC THREE-DIMENSIONAL MULTI-GROUP NEUTRINO RADIATION-HYDRODYNAMICS SIMULATIONS OF CORE-COLLAPSE SUPERNOVAE

ABSTRACT We report on a set of long-term general-relativistic three-dimensional (3D) multi-group (energy-dependent) neutrino radiation-hydrodynamics simulations of core-collapse supernovae. We employ a full 3D two-moment scheme with the local M1 closure, three neutrino species, and 12 energy groups per species. With this, we follow the post-core-bounce evolution of the core of a nonrotating progenitor in full unconstrained 3D and in octant symmetry for ≳380 ms. We find the development of an asymmetric runaway explosion in our unconstrained simulation. We test the resolution dependence of our results and, in agreement with previous work, find that low resolution artificially aids explosion and leads to an earlier runaway expansion of the shock. At low resolution, the octant and full 3D dynamics are qualitatively very similar, but at high resolution, only the full 3D simulation exhibits the onset of explosion.

Performance enhancement of fin attached ice-on-coil type thermal storage tank for different fin orientations using constrained and unconstrained simulations

One of the drawbacks in latent thermal energy storage system is the slow charging and discharging time due to the low thermal conductivity of the phase change materials (PCM). This study numerically investigated the PCM melting process inside a finned tube to determine enhanced heat transfer performance. The influences of fin length and fin numbers were investigated. Also, two different fin orientations, a vertical and horizontal type, were examined, using two different simulation methods, constrained and unconstrained. The unconstrained simulation, which considers the density difference between the solid and liquid PCM showed approximately 40 % faster melting rate than that of constrained simulation. For a precise estimation of discharging performance, unconstrained simulation is essential. Thermal instability was found in the liquid layer below the solid PCM, which is contrary to the linear stability theory, due to the strong convection driven by heat flux from the coil wall. As the fin length increases, the area affected by the fin becomes larger, thus the discharging time becomes shorter. The discharging performance also increased as the fin number increased, but the enhancement of discharging performance by more than two fins was not discernible. The horizontal type shortened the complete melting time by approximately 10 % compared to the vertical type.

A direct search method for unconstrained quantile-based simulation optimization

Simulation optimization has gained popularity over the decades because of its ability to solve many practical problems that involve profound randomness. The methodology development of simulation optimization, however, is largely concerned with problems whose objective function is mean-based performance metric. In this paper, we propose a direct search method to solve the unconstrained simulation optimization problems with quantile-based objective functions. Because the proposed method does not require gradient estimation in the search process, it can be applied to solve many practical problems where the gradient of objective function does not exist or is difficult to estimate. We prove that the proposed method possesses desirable convergence guarantee, i.e., the algorithm can converge to the true global optima with probability one. An extensive numerical study shows that the performance of the proposed method is promising. Two illustrative examples are provided in the end to demonstrate the viability of the proposed method in real settings.

Study of curcumin behavior in two different lipid bilayer models of liposomal curcumin using molecular dynamics simulation

Liposomal formulation of curcumin is an important therapeutic agent for the treatment of various cancers. Despite extensive studies on the biological effects of this formulation in cancer treatment, much remains unknown about curcumin–liposome interactions. Understanding how different lipid bilayers respond to curcumin molecule may help us to design more effective liposomal curcumin. Here, we used molecular dynamics simulation method to investigate the behavior of curcumin in two lipid bilayers commonly used in preparation of liposomal curcumin, namely dipalmitoylphosphatidylcholine (DPPC) and dimyristoylphosphatidylglycerol (DMPG). First, the free energy barriers for translocation of one curcumin molecule from water to the lipid bilayer were determined by using the potential of mean force (PMF). The computed free energy profile exhibits a global minimum at the solvent–headgroup interface (LH region) for both lipid membranes. We also evaluated the free energy difference between the equilibrium position of curcumin in the lipid bilayer and bulk water as the excess chemical potential. Our results show that curcumin has the higher affinity in DMPG compared to DPPC lipid bilayer (−8.39 vs. −1.69 kBT) and this is related to more hydrogen bond possibility for curcumin in DMPG lipid membrane. Next, using an unconstrained molecular dynamic simulation with curcumin initially positioned at the center of lipid bilayer, we studied various properties of each lipid bilayer system in the presence of curcumin molecule that was in full agreement with PMF and experimental data. The results of these simulation studies suggest that membrane composition could have a large effect on interaction of curcumin–lipid bilayer.

The Application of Facies Modeling Combination of Well Data and Seismic Data in G25-12 Block

The main purpose of lithofacies modeling is to get the actual reservoir lithofacies skeleton model which is maximum approximation of the underground reservoir. The facies model can effectively solve the problem of predicting sand bodies between wells. At the same time, we still use the stochastic modeling method to build the facies model of unconstrained single well simulation and sedimentary facies controlled constrained simulation. We elected the model which is most consistent to the actual geological conditions, providing theoretical guidance for characterizing the interwell sand body distribution law and improving the accuracy of predicting sand bodies between wells, laiding the foundation for further exploration and development of oil reservoir.

Binding pathway of histamine to the hH4R, observed by unconstrained molecular dynamics.

Histamine binds with high affinity to the human histamine H4 receptor (hH4R). We are the first to examine the complete binding pathway of histamine from the extracellular side to the orthosteric binding site of the hH4R by means of unconstrained molecular dynamic simulation. Furthermore, the simulations show that the positively charged amine moiety of the histamine interacts electrostatically with the highly conserved Asp(3.32), while the imidazole moiety forms a hydrogen bond interaction with Glu(5.46) and Gln(7.42).

Structural modifications of 4-aryl-4-oxo-2-aminylbutanamides and their acetyl- and butyrylcholinesterase inhibitory activity. Investigation of AChE–ligand interactions by docking calculations and molecular dynamics simulations

Congeneric set of thirty-eight 4-aryl-4-oxo-2-(N-aryl/cycloalkyl)butanamides has been designed, synthesized and evaluated for acetyl- and butyrylcholinesterase inhibitory activity. Structural variations included cycloalkylamino group attached to C2 position of butanoyl moiety, and variation of amido moiety of molecules. Twelve compounds, mostly piperidino and imidazolo derivatives, inhibited AChE in low micromolar range, and were inactive toward BChE. Several N-methylpiperazino derivatives showed inhibition of BChE in low micromolar or submicromolar concentrations, and were inactive toward AChE. Therefore, the nature of the cycloalkylamino moiety governs the AChE/BChE selectivity profile of compounds. The most active AChE inhibitor showed mixed-type inhibition modality, indicating its binding to free enzyme and to enzyme–substrate complex. Thorough docking calculations of the seven most potent AChE inhibitors from the set, showed that the hydrogen bond can be formed between amide –NH– moiety of compounds and –OH group of Tyr 124. The 10 ns unconstrained molecular dynamic simulation of the AChE–compound 18 complex shows that this interaction is the most persistent. This is, probably, the major anchoring point for the binding.

On the time‐mean state of ocean models and the properties of long range acoustic propagation

Receptions on three vertical hydrophone arrays from basin‐scale acoustic transmissions in the North Pacific during 1996 and 1998 are used to test the time‐mean sound‐speed properties of the World Ocean Atlas 2005 (WOA05), of an eddying unconstrained simulation of the Parallel Ocean Program (POP), and of three data‐constrained solutions provided by the estimating the circulation and climate of the ocean (ECCO) project: a solution based on an approximate Kalman filter from the Jet Propulsion Laboratory (ECCO‐JPL), a solution based on the adjoint method from the Massachusetts Institute of Technology (ECCO‐MIT), and an eddying solution based on a Green's function approach from ECCO, Phase II (ECCO2). Predictions for arrival patterns using annual average WOA05 fields match observations to within small travel time offsets (0.3–1.0 s). Predictions for arrival patterns from the models differ substantially from the measured arrival patterns, from the WOA05 climatology, and from each other, both in terms of travel time and in the structure of the arrival patterns. The acoustic arrival patterns are sensitive to the vertical gradients of sound speed that govern acoustic propagation. Basin‐scale acoustic transmissions, therefore, provide stringent tests of the vertical temperature structure of ocean state estimates. This structure ultimately influences the mixing between the surface waters and the ocean interior. The relatively good agreement of the acoustic data with the more recent ECCO solutions indicates that numerical ocean models have reached a level of accuracy where the acoustic data can provide useful additional constraints for ocean state estimation.