Future Simulations Research Articles

Dissipated correction map method with trapezoidal rule for the simulations of gravitational waves from spinning compact binary

ABSTRACT The correction map method means extended phase-space algorithm with correction map. In our research, we have developed a correction map method, specifically the dissipated correction map method with trapezoidal rule, for numerical simulations of gravitational waves from spinning compact binary systems. This new correction map method, denoted as $CM3$, has shown remarkable performance in various simulation results, such as phase-space distance, dissipated energy error, and gravitational waveform, closely resembling the high-order precision implicit Gaussian algorithm. When compared with the previously used mid-point map which is denoted as $C_2$, the $CM3$ consistently exhibits a closer alignment with the highly accurate Gaussian algorithm in waveform evolution and orbital trajectory analysis. Through detailed comparisons and analyses, it is evident that $CM3$ outperforms other algorithms, including $CM2$ and $C_2$ mentioned in this paper, in terms of accuracy and precision in simulating spinning compact binary systems. The incorporation of the trapezoidal rule and the optimization with a scale factor $\gamma$ have significantly enhanced the performance of $CM3$, making it a promising method for future numerical simulations in astrophysics. With the groundbreaking detection of gravitational waves by the LIGO/VIRGO collaboration, interest in this research domain has soared. Our work contributes valuable insights for the application of matched filtering techniques in the analysis of gravitational wave signals, enhancing the precision and reliability of these detection.

Spatio-temporal characteristics and multi-scenario simulation analysis of ecosystem service value in coastal wetland: A case study of the coastal zone of Hainan Island, China

Coastal wetland ecosystems harbor rich biodiversity and possess significant ecosystem service value (ESV). Therefore, it offers a range of crucial ecosystem services (ES) for human well-being and socio-economic development. Taking the Hainan Island coastal zone (HICZ) as a case study, the spatio-temporal characteristics of land use and land cover change (LULCC), and its associated ESV in wetland landscapes were analyzed over three time points (2000, 2010 and 2020). We explored the spatio-temporal evolution trajectory of ESV on the basis of geo-information tupu. Then, future land use simulation (FLUS) was employed to predict wetland patterns and ESV under three different scenarios: business as usual (BAU), ecological conservation first (ECF), and economic development first (EDF). The results showed that over the past two decades, a significant proportion (exceeding 80%) of the overall wetland region was comprised of offshore and coastal wetlands (OCW) as well as constructed wetlands (CW); these formed the matrix of the landscape. The area of building land (BL) continued to exhibit a consistent upward trend. Expanding by 2.18 times, it represented the most significant increase in the rate of dynamic changes in BL. The main ES in the HICZ corresponded to the regulation services (53.57%) and the support services (27.58%). The ESV of wetland losses accounted for 45.17% (43.08 × 108 yuan) of the total loss. The spatial differentiation of ESV in the HICZ was larger in the southwest and the northeast regions, while it was comparatively lower in the north. The transformation in the area of early and late change types accounted for 236.46 km2 and 356.69 km2, respectively. The scenario ECF was achieved with an optimal development of ESV (1807.72 × 108 yuan), which was coordinated with the high-level of development of regional ES functions and the economy. These findings provide valuable information for the sustainable development as well as the protection of ecology and environment of the coastal zone under the background of the construction of Hainan pilot free trade zone in the future.

Addressing the impact of land use land cover changes on land surface temperature using machine learning algorithms

Over the past two and a half decades, rapid urbanization has led to significant land use and land cover (LULC) changes in Kabul province, Afghanistan. To assess the impact of LULC changes on land surface temperature (LST), Kabul province was divided into four LULC classes applying the Support Vector Machine (SVM) algorithm using the Landsat satellite images from 1998 to 2022. The LST was assessed using Landsat data from the thermal band. The Cellular Automata-Logistic Regression (CA-LR) model was applied to predict the future patterns of LULC and LST for 2034 and 2046. Results showed significant changes in LULC classes, as the built-up areas increased about 9.37%, while the bare soil and vegetation cover decreased 7.20% and 2.35%, respectively, from 1998 to 2022. The analysis of annual LST revealed that built-up areas showed the highest mean LST, followed by bare soil and vegetation. The future simulation results indicate an expected increase in built-up areas to 17.08% and 23.10% by 2034 and 2046, respectively, compared to 11.23% in 2022. Similarly, the simulation results for LST indicated that the area experiencing the highest LST class (≥ 32 °C) is expected to increase to 27.01% and 43.05% by 2034 and 2046, respectively, compared to 11.21% in 2022. The results indicate that LST increases considerably as built-up areas increase and vegetation cover decreases, revealing a direct link between urbanization and rising temperatures.

Multi-cycle Direct Numerical Simulations of a Laboratory Scale Engine: Evolution of Boundary Layers and Wall Heat Flux

AbstractMulti-cycle direct numerical simulations (DNS) of a laboratory-scale engine at technically relevant engine speeds (1500 and 2500 rpm) are performed to investigate the transient velocity and thermal boundary layers (BL) as well as the wall heat flux during the compression stroke under motored operation. The time-varying wall-bounded flow is characterized by a large-scale tumble vortex, which generates vortical structures as the flow rolls off the cylinder wall. The bulk flow is found to strongly affect the development of the BL profiles, especially at higher engine speeds. As a result, the large-scale flow structures lead to alternating pressure gradients near the wall, invalidating the flow equilibrium assumptions used in typical wall modeling approaches. The thickness of the velocity BL and of the viscous sublayer was found to scale inversely with engine speed and crank angle. The thermal BL thickness also scales inversely with engine speed but increases with in-cylinder temperature. In contrast, thermal displacement thickness, which is sometimes used as a proxy for thermal BL thickness, was found to decrease with increasing temperature in the bulk. Examination of the heat flux distribution revealed areas of increased heat flux, particularly at places characterized by strong flow directed towards the wall. In addition, significant cyclic variations in the surface-averaged wall heat flux were observed for both engine speeds. An analysis of the cyclic tumble ratio revealed that the cycles with lower tumble ratio values near top dead center (TDC), indicative of an earlier tumble breakdown, also exhibit higher surface averaged wall heat fluxes. These findings extend previous numerical and experimental results for the evolution of BL structure during the compression stroke and serve as an important step for future engine simulations under realistic operating conditions.

Evolution of megadrought and pluvial events in the Qaidam Basin and Hexi Corridor, Northwest China, during the period 455–2100 CE

AbstractMillennium‐long hydroclimate reconstructions in the Qaidam Basin (QB) and Hexi Corridor (HXC) suggest markedly differing moisture change trends between the two regions in the 20th century; however, it remains unclear whether these current moisture states are exceptional in a long‐term context, and how megadrought and pluvial events have evolved in these regions. Here, we used previously published historical hydroclimate reconstructions combined with model‐based future moisture simulations to assess past, current and future hydroclimate anomalies in a long‐term context (i.e., 455–2100 CE), and investigate the evolution of megadrought and pluvial events. Compared with the QB, moisture variability in the HXC was higher and more prone to the occurrence of severe and long‐lasting megadrought and pluvial events. Megadroughts in the QB mainly occurred in the Little Ice Age (1200–1800 CE) accompanied by lower temperatures, whereas in the HXC, megadroughts mostly occurred during the Medieval Climate Anomaly (800–1200 CE) accompanied by higher temperatures. The Significant Zero crossing of derivatives (SiZer) and Time of Emergence (TOE) analyses were used to reveal the initiation of recent humidity changes and the duration above the natural variability threshold. We found that the QB has experienced a significant wetting trend since the middle of the 20th century, with this trend exceeding the range of natural hydroclimate variability in 1975 CE. The HXC became drier from the early 20th century, but has become wetter since the late 20th century; this trend may exceed the natural hydroclimate variability range by 2032 CE. We also found that the duration and severity of megadrought and pluvial events are positively correlated in each region. Given the higher past hydrological variability in the HXC compared with the QB, our study implies that future extreme hydrological events are more likely to occur in the former of these two regions.

The Influence of ENSO Diversity on Future Atlantic Tropical Cyclone Activity

Abstract El Niño–Southern Oscillation (ENSO) influences seasonal Atlantic tropical cyclone (TC) activity by impacting environmental conditions important for TC genesis. However, the influence of future climate change on the teleconnection between ENSO and Atlantic TCs is uncertain, as climate change is expected to impact both ENSO and the mean climate state. We used the Weather Research and Forecasting Model on a tropical channel domain to simulate 5-member ensembles of Atlantic TC seasons in historical and future climates under different ENSO conditions. Experiments were forced with idealized sea surface temperature configurations based on the Community Earth System Model (CESM) Large Ensemble representing: a monthly varying climatology, eastern Pacific El Niño, central Pacific El Niño, and La Niña. The historical simulations produced fewer Atlantic TCs during eastern Pacific El Niño compared to central Pacific El Niño, consistent with observations and other modeling studies. For each ENSO state, the future simulations produced a similar teleconnection with Atlantic TCs as in the historical simulations. Specifically, La Niña continues to enhance Atlantic TC activity, and El Niño continues to suppress Atlantic TCs, with greater suppression during eastern Pacific El Niño compared to central Pacific El Niño. In addition, we found a decrease in the Atlantic TC frequency in the future relative to historical regardless of ENSO state, which was associated with a future increase in northern tropical Atlantic vertical wind shear and a future decrease in the zonal tropical Pacific sea surface temperature (SST) gradient, corresponding to a more El Niño–like mean climate state. Our results indicate that ENSO will remain useful for seasonal Atlantic TC prediction in the future.

Bayesian hierarchical model for bias-correcting climate models

Abstract. Climate models, derived from process understanding, are essential tools in the study of climate change and its wide-ranging impacts. Hindcast and future simulations provide comprehensive spatiotemporal estimates of climatology that are frequently employed within the environmental sciences community, although the output can be afflicted with bias that impedes direct interpretation. Post-processing bias correction approaches utilise observational data to address this challenge, although they are typically criticised for not being physically justified and not considering uncertainty in the correction. This paper proposes a novel Bayesian bias correction framework that robustly propagates uncertainty and models underlying spatial covariance patterns. Shared latent Gaussian processes are assumed between the in situ observations and climate model output, with the aim of partially preserving the covariance structure from the climate model after bias correction, which is based on well-established physical laws. Results demonstrate added value in modelling shared generating processes under several simulated scenarios, with the most value added for the case of sparse in situ observations and smooth underlying bias. Additionally, the propagation of uncertainty to a simulated final bias-corrected time series is illustrated, which is of key importance to a range of stakeholders, such as climate scientists engaged in impact studies, decision-makers trying to understand the likelihood of particular scenarios and individuals involved in climate change adaption strategies where accurate risk assessment is required for optimal resource allocation. This paper focuses on one-dimensional simulated examples for clarity, although the code implementation is developed to also work on multi-dimensional input data, encouraging follow-on real-world application studies that will further validate performance and remaining limitations. The Bayesian framework supports uncertainty propagation under model adaptations required for specific applications, providing a flexible approach that increases the scope of data assimilation tasks more generally.

New experimental method for the simultaneous determination of concentration and size profiles of condensed combustion products around a burning aluminum droplet

When an aluminum particle burns in the diffusive regime, a cloud of nanometric particles of its primary oxide, alumina, is formed around the droplet. Characterizing this oxide smoke surrounding a burning aluminum droplet is essential. The original contribution of this paper is to introduce an experimental approach that allows for simultaneous size and concentration measurement of the particles composing the oxide smoke. This paper employs an electrodynamic levitator to facilitate the self-sustained combustion of an isolated aluminum particle, with a radius of 35μm, in atmospheric air. This levitation apparatus is paired with an optical setup that allows for a multi-spectral light extinction method. This technique is specifically designed to measure the size and concentration of alumina particles below the micrometric scale, which is scarcely documented in existing literature. Consequently, spatially resolved concentration and size profiles of the nanometric alumina particles are measured and compared to simulated data from the literature. The radii of alumina particles in the cloud are found to evolve closely around 80 nm. Volume fractions are evaluated from 2.8⋅10−4 near the particle surface to 3⋅10−5 further in the cloud. Therefore, significant concentrations of alumina particles are revealed during the short (15 to 20 ms) combustion process at distances of the order of magnitude of a few initial particle diameters. Such characterization could then lead to a better assessment of the interaction distance among aluminum particles as they burn collectively.Novelty and significance statementThis article introduces the first experimentally determined profiles of alumina concentration and size distribution surrounding a single burning aluminum droplet. The uniqueness of our experimental setup lies in its ability to study of the most fundamental case of the autonomous combustion of a single levitating particle, without any convective effects. A new non-intrusive method specifically designed provides unprecedented results in the field of metallic particle combustion. Data provided in the paper are crucial as they serve as the first reference case for future simulation and experiments. The results introduced in this paper highlight the inability of current simulation methods to accurately account for nucleation and condensation processes, and emphasize the need for a non-invasive characterization method.

Thermal Properties of 3D-Printed Molds for Light Metal Casting

AbstractBinder Jetting technology is well established for the production of sand molds and cores for foundry use, owing to its flexibility and expansive design capabilities. A wide array of sand, aggregate, and binder combinations is commercially available. Utilizing these types of refractory materials in the casting process presents both technical and economic benefits and drawbacks. For intricate cast components, foundry technologists must assess the thermophysical properties of the mold material systems. With this knowledge, specialized high-performance material combinations may be employed in specific areas of the mold, while more economically viable systems are used for shaping the external mold support. This study primarily focuses on determining the heat capacity and thermal diffusivity and consequently the thermal conductivity using a specially developed analytical method. It investigates three different fundamental aggregates: silica, cerabeads®, and chromite. The result’s range provides an overview of relevant characteristics for the selected material systems. Given that the properties of sand affect heat flow during casting and solidification, these newly determined values can be utilized in future simulations. Consequently, these findings aid in maintaining and enhancing the quality of critically stressed cast parts.

Adapting arepo-rt for exascale computing: GPU acceleration and efficient communication

ABSTRACT Radiative transfer (RT) is a crucial ingredient for self-consistent modelling of numerous astrophysical phenomena across cosmic history. However, on-the-fly integration into radiation hydrodynamics (RHD) simulations is computationally demanding, particularly due to the stringent time-stepping conditions and increased dimensionality inherent in multifrequency collisionless Boltzmann physics. The emergence of exascale supercomputers, equipped with extensive CPU cores and GPU accelerators, offers new opportunities for enhancing RHD simulations. We present the first steps towards optimizing arepo-rt for such high-performance computing environments. We implement a novel node-to-node (n-to-n) communication strategy that utilizes shared memory to substitute intranode communication with direct memory access. Furthermore, combining multiple internode messages into a single message substantially enhances network bandwidth utilization and performance for large-scale simulations on modern supercomputers. The single-message n-to-n approach also improves performance on smaller scale machines with less optimized networks. Furthermore, by transitioning all RT-related calculations to GPUs, we achieve a significant computational speedup of around 15 for standard benchmarks compared to the original CPU implementation. As a case study, we perform cosmological RHD simulations of the Epoch of Reionization, employing a similar setup as the THESAN project. In this context, RT becomes sub-dominant such that even without modifying the core arepo codebase, there is an overall threefold improvement in efficiency. The advancements presented here have broad implications, potentially transforming the complexity and scalability of future simulations for a wide variety of astrophysical studies. Our work serves as a blueprint for porting similar simulation codes based on unstructured resolution elements to GPU-centric architectures.

Research Progress on Numerical Simulation of the Deposition and Deformation Behavior of Cold Spray Particles

It is of significant theoretical and practical value to study the deposition process and deformation behavior of cold-sprayed particles to find the deposition mechanism of cold-sprayed coatings, further improve the coating performance, and expand its application scope. However, observing the deposition process and particle behavior through experiments is difficult due to the brief deposition duration of cold spray particles. Numerical simulation offers a means to slow the deposition process and predict the critical velocity, deformation behavior, bonding mechanism, and residual stress of cold-sprayed particles. This paper uses finite element analysis software, including ANSYS LS Dynamic-2022 R1 and ABAQUS-6.14, alongside various prevalent finite element methods for numerically simulating cold spray particle deposition. These methods involve the Lagrange, Euler, arbitrary Lagrange-Euler (ALE), and Smoothed Particle Hydrodynamics (SPH) to investigate the cold spray particle deposition process. The recent literature primarily summarizes the simulation outcomes achieved by applying these methodologies for simulating the deposition process and deformation characteristics of different particles under varying cold spraying conditions. In addition, the reliability of these simulation results is analyzed by comparing the consistency between the simulation results of single-particle and multi-particle and the actual experimental results. On this basis, these methods’ advantages, disadvantages, and applicability are comprehensively analyzed, and the future simulation research work of particle deposition process and deformation behavior of cold spraying prospects is discussed. Future research is expected to provide a more in-depth study of the micro-mechanisms, such as the evolution of the inter-particle and internal organization of the particles, near the actual situation.

Quantum extreme learning of molecular potential energy surfaces and force fields

Quantum machine learning algorithms are expected to play a pivotal role in quantum chemistry simulations in the immediate future. One such key application is the training of a quantum neural network to learn the potential energy surface and force field of molecular systems. We address this task by using the quantum extreme learning machine paradigm. This particular supervised learning routine allows for resource-efficient training, consisting of a simple linear regression performed on a classical computer. We have tested a setup that can be used to study molecules of any dimension and is optimized for immediate use on NISQ devices with a limited number of native gates. We have applied this setup to three case studies: lithium hydride, water, and formamide, carrying out both noiseless simulations and actual implementation on IBM quantum hardware. Compared to other supervised learning routines, the proposed setup requires minimal quantum resources, making it feasible for direct implementation on quantum platforms, while still achieving a high level of predictive accuracy compared to simulations. Our encouraging results pave the way towards the future application to more complex molecules, being the proposed setup scalable.

Construction of Ecological Security Patterns and Evaluation of Ecological Network Stability under Multi-Scenario Simulation: A Case Study in Desert–Oasis Area of the Yellow River Basin, China

Land use change has a significant impact on the sustainability of ecosystems, and ecological security patterns (ESPs) can improve environmental quality through spatial planning. This study explored a multi-scenario ESP framework by integrating future land use simulation (FLUS) and minimum cumulative resistance (MCR) for urban agglomeration along the Yellow River Basin (YRB) in Ningxia. The research involved simulating land use change in 2035 under four development scenarios, identifying ecological security networks, and evaluating network stability for each scenario. The study revealed that the ecological sources under different development scenarios, including a natural development scenario (NDS), an economic development scenario (EDS), a food security scenario (FSS), and an ecological protection scenario (EPS), were 834.82 km2, 715.46 km2, 785.56 km2, and 1091.43 km2, respectively. The overall connectivity values (OG) for these scenarios were 0.351, 0.466, 0.334, and 0.520, respectively. It was found that under an EPS, the ESPs had the largest area of ecological sources and the most stable ecological network structure, which can effectively protect natural habitats. This study provides a valuable method for identifying ESPs that can respond to diversity and the uncertainty of future development. It can assist decision-makers in enhancing the ecological quality of the study area while considering various development scenarios.

The promotion of sustainable land use planning for the enhancement of ecosystem service capacity: Based on the FLUS-INVEST-RUSLE-CASA model.

Land Use/Land Cover (LULC) is one of the most significant human variables influencing the efficiency of Ecosystem Services (ESs) in terrestrial ecosystems. Theoretical and technical assistance for regional sustainable land use planning and management, as well as ecosystem conservation and restoration, is provided by investigating the influence of changes in the LULC pattern on the efficiency of ESs. This research focuses on the interactions between socioeconomic activities and natural ecological processes in the Three Gorges Reservoir Area (TGRA). We use LULC data from the TGRA for the years 1990, 2000, 2010, and 2020. The study includes the analysis and calculation of the spatiotemporal evolution features of the current LULC pattern and the efficiency of ESs, including their spatiotemporal distribution. Considering the TGRA's national development orientation and guidance, three potential LULC patterns are constructed under various develop-ment scenarios. To calculate the efficiency of ESs, the GeoSOS-FLUS future LULC simulation model is linked, and several methodologies such as INVEST, RUSLE, and CASA are used. The goal is to investigate the influence of future changes in LULC patterns on ESs efficiency. The findings show the following: (1) From 1990 to 2020, the values of water conservation services in the TGRA decreased and subsequently increased. High-value areas are primarily located in the reservoir's centre and eastern sections, whereas low-value areas are mostly found in the western section. Soil conservation service values initially declined and later climbed. The TGRA's carbon storage services have in-creased yearly, from 552.64 g/m2 in 2000 to 615.92 g/m2 in 2020. (2) In the ecological protection scenario, carbon storage and soil erosion increased compared to the ecosystem services in 2020. The ecological system service benefits are greater when compared to the natural development scenario. (3) The four ESs show positive spatial correlations across all three scenarios, and local spatial au-tocorrelation analysis findings demonstrate that carbon storage, water yield, and habitat quality have comparable spatial distributions across all three scenarios. To some extent, high-value areas for water conservation, soil retention, carbon storage, and habitat quality overlap.

Mechanical deformation and death of circulating tumor cells in thebloodstream.

The circulation of tumor cells through the bloodstream is a significant step in tumor metastasis. To better understand the metastatic process, circulating tumor cell (CTC) survival in the circulation must be explored. While immune interactions with CTCs in recent decades have been examined, research has yet to sufficiently explain some CTC behaviors in blood flow. Studies related to CTC mechanical responses in the bloodstream have recently been conducted to further study conditions under which CTCs might die. While experimental methods can assess the mechanical properties and death of CTCs, increasingly sophisticated computational models are being built to simulate the blood flow and CTC mechanical deformation under fluid shear stresses (FSS) in the bloodstream.Several factors contribute to the mechanical deformation and death of CTCs as they circulate. While FSS can damage CTC structure, diverse interactions between CTCs and blood components may either promote or hinder the next metastatic step-extravasation at a remote site. Overall understanding of how these factors influence the deformation and death of CTCs could serve as a basis for future experiments and simulations, enabling researchers to predict CTC death more accurately. Ultimately, these efforts can lead to improved metastasis-specific therapeutics and diagnostics specific in the future.

Qualifying uncertainty of precipitation projections over China: mitigating uncertainty with emergent constraints

Predicting future mean precipitation poses significant challenges due to uncertainties among climate models, complicating water resource management. In this study, we introduce a novel methodology to mitigate uncertainty in future mean precipitation projections over China on a grid-by-grid basis. By constraining precipitation parameters of the Gamma distribution, we establish emergent constraints on parameters, revealing significant correlations between historical and future simulations. Our analysis spans the periods 2040–2069 and 2070–2099 under low-to-moderate and high emission scenarios. We observe reductions in uncertainty across most regions of China, with constrained mean precipitation indicating increases in monsoon regions and decreases in non-monsoon zones relative to raw projections. Notably, the observed 30%–40% increase in mean precipitation for the whole of China underscores the efficacy of our methodology. These observationally constrained results provide valuable insights into current precipitation projections, offering actionable information for water resource planning and climate adaptation strategies amidst future uncertainties.

What drives the corpulence of galaxies?

Nearby dwarf galaxies display a variety of effective radii (sizes) at a given stellar mass, suggesting different evolution scenarios according to their final “stellar” size. The TNG hydrodynamical simulations present a bimodality in the z = 0 size–mass relation (SMRz0) of dwarf galaxies, at r1/2, ⋆ ∼ 450 pc. Using the TNG50 simulation, we explored the evolution of the most massive progenitors of dwarf galaxies (z = 0 log(M⋆/M⊙) between 8.4 and 9.2) that end up as central galaxies of their groups. We split these dwarfs into three classes of the SMRz0: “Normals” from the central spine of the main branch, and “Compacts” from the secondary branch as well as the lower envelope of the main branch. Both classes of Compacts see their stellar sizes decrease from z ∼ 1 onwards in contrast to Normals, while the sizes of the gas and dark matter (DM) components continue to increase (as for Normals). A detailed analysis reveals that Compacts live in poorer environments, and thus suffer fewer major mergers from z = 0.8 onwards, which otherwise would pump angular momentum into the gas, allowing strong gas inflows, producing inner star formation, and thus leading to the buildup of a stellar core. Compacts are predicted to be rounder and to have bluer cores. Compact dwarfs of similar sizes are observed in the GAMA survey, but the bimodality in size is less evident and the most compact dwarfs tend to be passive rather than star forming, as in TNG50. Our conclusions should therefore be confirmed with future cosmological hydrodynamical simulations.

Future land use and land cover simulations with cellular automata-based artificial neural network: A case study over Delhi megacity (India)

According to United Nations projections, future global urban growth will mostly occur in Asian megacities. In this study, a Cellular Automata based Artificial Neural Network (CA-ANN) model is used to simulate the future land use and land cover (LULC) over Delhi megacity (India). Delhi, projected to become the world's most populated city by 2030, is an example of a data poor city in Asia, having millions of climate vulnerable people. The CA-ANN model of Modules for Land Change Simulation (MOLUSCE), an open-source plugin, is first tested to simulate the LULC for 2009. Based on good validation results-structural similarity (SSIM; 0.8288), overall accuracy (79.78 %), kappa index of agreement (KIA; 77.25 %), and minimum validation overall error (0.0379), the same model set-up is used to carry out LULC simulation for 2030. This model is found to be simple, efficient, and computationally less expensive tool, and can be used to model future LULCs with a minimal set of inputs, a constraint often found in data poor cities. Results show continued increase in built-up area from 38.3 % (2014) to 53.8 % (2030), at the expense of cultivable areas, forests, and wastelands. The study incorporates past and future LULC change trajectories to highlight the changing LULC dynamics of the megacity from 1977 to 2030. Rate of urban sprawl, calculated using compound annual growth rate (CAGR) is projected to be 2.51 % for 2014–2030, substantially higher than the estimates for 2006–2014 (0.62 %). Further, the past and future urban growth patterns for Delhi are found to mimic other big Asian cities. The database generated from the present study has wide applicability for scientific research community, governmental bodies, profit and non-profit organizations for topics concerning-future urban climate research, climate risk and adaption policy frameworks, climate finance budgeting, future town planning, etc.

Interlinking Rayleigh–Taylor/Richtmyer–Meshkov interfacial mixing with variable acceleration and canonical Kolmogorov turbulence

Canonical turbulence and Rayleigh–Taylor/Richtmyer–Meshkov mixing with variable acceleration are paradigmatic complexities in science, mathematics, and engineering, with broadly ranging applications in nature, technology, and industry. We employ scaling symmetries and invariant forms to represent these challenging processes and to assess their very different properties. We directly link—for the first time to our knowledge—the attributes of Rayleigh–Taylor/Richtmyer–Meshkov interfacial mixing with variable acceleration to those of canonical turbulence, including scaling laws, spectral shapes, and characteristic scales. We explore the role of control dimensional parameters in quantifying these processes. The theory results compare well with available observations, the chart perspectives for future experiments and simulations, and for better understanding realistic complexity.

The future of project management simulation exercises

In recent times project management has become among the most popular post graduate courses at UK Universities particularly for international students. Students consider the skill set useful for employability and transferable for a wide range of future avenues helpful in an uncertain world. However, many start this course with no workplace experience and many of the project management concepts are difficult to grasp or cannot be fully tested except within a realistic project situation. Hence project management simulations or games have become increasingly popular to help resolve this issue. This research study focuses on evaluating the effectiveness of a project management simulation exercise used by a leading UK University within their project management teaching programme at post-graduate level. A review of the literature included recent studies of simulation, the development of project management education thinking, experiential learning theory and the skill set required from modern project managers from the perspective of professional bodies, industry groups and academics. This produced a list of 17 skills or competences or knowledge areas including both hard skills such as schedule management and risk management and soft skills such as communication, collaboration, and innovation. Students from the 2021-22 academic year produced quantitative data via a survey relating to their self-perception of their skill level before and after the simulation. Tutors were interviewed to obtain a deeper insight into the mechanisms of learning, the conditions required and their thoughts on future simulation design development. This qualitative data was used to develop a conceptual model for future project management simulation design. The results show that from the student perspective this learning approach is highly effective with in almost all cases the level of competence started at below average and ended at above average after the simulation. Students consider this approach memorable and enjoyable, were fully engaged and would recommend to their peers. The problem of self-assessment was discussed but a link between student confidence and employability proposed. The conceptual model developed from the qualitative data includes not only simulation design but also game management and tutor skill development. Collaboration between industry partners, game developers and educationalists is proposed to develop the next generation of project management simulation exercises.