Effectiveness Of Various Control Strategies Research Articles

Comparative analysis of control strategies impact on power losses in IGBT power modules with a multiphysics‐circuit coupling method

AbstractPower losses in semiconductor devices present a significant impediment to advancing power electronics systems for achieving higher frequencies, improved efficiency, and greater integration. A major challenge lies in directly coupling power losses with various control strategies, considering the variations in manufacturers, packaging, and process structures within the power electronics field. This paper introduces a field‐circuit coupling simulation methodology of the insulated gate bipolar transistor (IGBT) within the Simulink/COMSOL environment, using a conventional three‐phase six‐switch voltage source inverter (VSI) IGBT module as a case study. A composite transfer function interconnects the electrical and thermal aspects, enabling bidirectional coupling between IGBT temperature and losses. This study aims to comprehensively compare the effects of various control strategies, namely, single‐vector, dual‐vector, and three‐vector current model predictive control (CMPC) and space vector pulse width modulation (SVPWM), on the losses and temperature of IGBT power modules. The findings emphasize that losses are significantly influenced by the selection of weighting factor coefficients and power factor settings under the same CMPC control strategy with a fixed switching frequency. Additionally, the selection of control strategies, such as CMPC and SVPWM, substantially impacts power losses in power electronic devices.

Evaluating the impact of double dose vaccination on SARS-CoV-2 spread through optimal control analysis

This paper presents a new nonlinear epidemic model for the spread of SARS-CoV-2 that incorporates the effect of double dose vaccination. The model is analyzed using qualitative, stability, and sensitivity analysis techniques to investigate the impact of vaccination on the spread of the virus. We derive the basic reproduction number and perform stability analysis of the disease-free and endemic equilibrium points. The model is also subjected to sensitivity analysis to identify the most influential model parameters affecting the disease dynamics. The values of the parameters are estimated with the help of the least square curve fitting tools. Finally, the model is simulated numerically to assess the effectiveness of various control strategies, including vaccination and quarantine, in reducing the spread of the virus. Optimal control techniques are employed to determine the optimal allocation of resources for implementing control measures. Our results suggest that increasing the vaccination coverage, adherence to quarantine measures, and resource allocation are effective strategies for controlling the epidemic. The study provides valuable insights into the dynamics of the pandemic and offers guidance for policymakers in formulating effective control measures.

Effectiveness evaluation of mosquito suppression strategies on dengue transmission under changing temperature and precipitation

Widespread resurgence of dengue outbreaks has seriously threatened the global health. Due to lack of treatments and vaccines, one key strategy in dengue control is to reduce the vector population size. As an environment-friendly mosquito control approach, releasing male mosquitoes transinfected with specific Wolbachia strain into the field to suppress the wild mosquito population size has become wildly accepted. The current study evaluates the effectiveness of this suppression strategy on dengue control under changing temperature and precipitation profiles. We formulate a mathematical model which includes larval intra-specific competition, the maturation period for mosquitoes, the extrinsic incubation period (EIP) and intrinsic incubation period (IIP). The persistence of mosquitoes and disease is discussed in terms of two basic reproduction numbers (RM and R0) and the release ratio pw. Further numerical simulations are carried out to not only validate theoretical results, but also provide interesting quantitative observations. Sensitivity analysis on the reproduction numbers, peak size, peak time and the final epidemic size is performed with respect to model parameters, which highlights effective control measures against dengue transmission. Moreover, by assuming temperature and precipitation dependent mosquito-related parameters, the model can be used to project the effectiveness of releasing Wolbachia-carrying males under climatic variations. It is shown that the effectiveness of various control strategies is highly dependent on the changing temperature and precipitation profiles. In particular, the model projects that it is most challenging to control the disease at the favorable temperature (around 27∼30∘C) and precipitation (5∼8mm/day) range, during which the basic reproduction number R0 is very high and more Wolbachia-infected males should be released.

Mathematical modeling and optimal control of tuberculosis spread among smokers with case detection

<p>Tuberculosis (TB) remains one of deadly infectious diseases worldwide. Smoking habits are a significant factor that can increase TB transmission rates, as smokers are more susceptible to contracting TB than nonsmokers. Therefore, a control strategy that focused on minimizing TB transmission among smokers was essential. The control of TB transmission was evaluated based on the case detection rate. Undetected TB cases often resulted from economic challenges, low awareness, negative stigma toward TB patients, and health system delay (HSD). In this study, we developed a mathematical model that captured the dynamics of TB transmission specifically among smokers, incorporating the effects of case detection. Our innovative approach lied in the integration of smoking behavior as a key factor in TB transmission dynamics, which has been underexplored in previous models. We analyzed the existence and stability of the TB model equilibrium based on the basic reproduction number. Additionally, parameter sensitivity analysis was conducted to identify the most influential factors in the spread of the disease. Furthermore, this study investigated the effectiveness of various control strategies, including social distancing for smokers, TB screening in high-risk populations, and TB treatment in low-income communities. By employing the Pontryagin maximum principle, we solved optimal control problems to determine the most effective combination of interventions. Simulation results demonstrated that a targeted combination of control measures can effectively reduce the number of TB-infected individuals.</p>

The effectiveness of various control strategies: An insight from a comparison modelling study

Several local outbreaks have occurred and been suppressed with the dynamic zero-COVID policy and widely promoted vaccination program implemented in China. The epidemic duration and final size vary significantly in different cities, which may be attributed to different implementation patterns and intensities of non-pharmaceutical interventions (NPIs). It’s important to capture the underlying mechanism to explore more efficient implementation patterns of NPIs in order to prevent the future resurgence. In this study, outbreaks caused by Delta variant in Xi’an, Yangzhou and Guangzhou in 2021 are chosen as the examples. A novel model dividing the population into three groups is proposed to describe the heterogeneity of control interventions. The model is calibrated and key parameters related to NPIs are estimated by using multi-source epidemic data. The estimation results show a lower transmission probability but a higher initial reproduction number in Xi’an. Sensitivity analysis are conducted to investigate the impact of various control measures in different epidemic phases. The results identify the vital role of enhancing closed-off management, strengthening tracing and testing intensities, on shortening the epidemic durations and reducing the final size. Further, we find that sufficiently implemented closed-off management would prevent the city from lockdown. Strengthening the tracing other than the testing strategy in the initial stage is more effective on containing the epidemic in a shorter duration with less infections.

System dynamic modelling of healthcare associated influenza -a tool for infection control

BackgroundThe transmission dynamics of influenza virus within healthcare settings are not fully understood. Capturing the interplay between host, viral and environmental factors is difficult using conventional research methods. Instead, system dynamic modelling may be used to illustrate the complex scenarios including non-linear relationships and multiple interactions which occur within hospitals during a seasonal influenza epidemic. We developed such a model intended as a support for health-care providers in identifying potentially effective control strategies to prevent influenza transmission.MethodsBy using computer simulation software, we constructed a system dynamic model to illustrate transmission dynamics within a large acute-care hospital. We used local real-world clinical and epidemiological data collected during the season 2016/17, as well as data from the national surveillance programs and relevant publications to form the basic structure of the model. Multiple stepwise simulations were performed to identify the relative effectiveness of various control strategies and to produce estimates of the accumulated number of healthcare-associated influenza cases per season.ResultsScenarios regarding the number of patients exposed for influenza virus by shared room and the extent of antiviral prophylaxis and treatment were investigated in relation to estimations of influenza vaccine coverage, vaccine effectiveness and inflow of patients with influenza. In total, 680 simulations were performed, of which each one resulted in an estimated number per season. The most effective preventive measure identified by our model was administration of antiviral prophylaxis to exposed patients followed by reducing the number of patients receiving care in shared rooms.ConclusionsThis study presents an system dynamic model that can be used to capture the complex dynamics of in-hospital transmission of viral infections and identify potentially effective interventions to prevent healthcare-associated influenza infections. Our simulations identified antiviral prophylaxis as the most effective way to control in-hospital influenza transmission.

Short-circuit modeling of three-phase 4-wire unbalanced networks in presence of single-phase photovoltaic systems

Due to the growing diffusion of single-phase Photovoltaic Systems (PVSs), the analysis of active unbalanced three-phase 4-wire distribution networks in short-circuit operating conditions is nowadays of great interest. However, this analysis is not trivial due to various factors (e.g., environmental conditions, inverter control system, limits of the inverter current, location and type of the fault, PVS self-protection systems) influencing the contribution of PVSs to the short-circuit conditions. Among these factors, the greatest challenge is to model the complex behavior of the inverter control system that must comply with actual and future grid requirements, or with national and international standards, in both normal and abnormal operating conditions.An analytical model based on the phase-coordinates approach is proposed in this paper to evaluate the short-circuit contributions of single-phase PVSs connected to unbalanced three-phase 4-wire LV distribution networks. The model of the PVSs takes into account the main factors that influence the PVS contributions, with particular attention to the model of the control system which injects reactive power to support grid voltage in normal operating conditions and to perform low-voltage ride-through (LVRT) dynamic grid support during the fault.In this paper, control systems for next-generation single-phase PVSs able to satisfy grid code requirements are explored; they include constant average active power control, constant active current control and constant peak current control. Extensive numerical experiments are presented with reference to the Cigrè European LV Distribution Network Benchmark, considering different fault types, effects of various control strategies and the evaluation of the impact of the PVSs in LVRT conditions w.r.t. the passive network, i.e., the network under fault with no installed PVSs.

Transmission dynamics of COVID-19 in Nepal: Mathematical model uncovering effective controls

While most of the countries around the globe are combating the pandemic of COVID-19, the level of its impact is quite variable among different countries. In particular, the data from Nepal, a developing country having an open border provision with highly COVID-19 affected country India, has shown a biphasic pattern of epidemic, a controlled phase (until July 21, 2020) followed by an outgrown phase (after July 21, 2020). To uncover the effective strategies implemented during the controlled phase, we develop a mathematical model that is able to describe the data from both phases of COVID-19 dynamics in Nepal. Using our best parameter estimates with 95% confidence interval, we found that during the controlled phase most of the recorded cases were imported from outside the country with a small number generated from the local transmission, consistent with the data. Our model predicts that these successful strategies were able to maintain the reproduction number at around 0.21 during the controlled phase, preventing 442,640 cases of COVID-19 and saving more than 1,200 lives in Nepal. However, during the outgrown phase, when the strategies such as border screening and quarantine, lockdown, and detection and isolation, were altered, the reproduction number raised to 1.8, resulting in exponentially growing cases of COVID-19. We further used our model to predict the long-term dynamics of COVID-19 in Nepal and found that without any interventions the current trend may result in about 18.76 million cases (10.70 million detected and 8.06 million undetected) and 89 thousand deaths in Nepal by the end of 2021. Finally, using our predictive model, we evaluated the effects of various control strategies on the long-term outcome of this epidemics and identified ideal strategies to curb the epidemic in Nepal.

Rumor model on homogeneous social network incorporating delay in expert intervention and government action

Rumors are spreading all over the network drastically, affecting millions of people in a minuscule instance. This malicious news can be a cause of panic, social unrest, political imbalance, and slow economic growth of the country. Epidemiological modeling is a valuable tool to describe not only the dynamics of rumor on a social network but also analyzing the effect of various control strategies for handling emergencies. The time delay is viewed as a latent period and immune period in epidemics. Similarly, time delay exists in rumor spreading on the social network not only to influence thinkers by rumor adopters but also in expert intervention and government policy. On the basis of these premises, we propose a computational mathematical model of malicious news dynamics on a homogeneous social network and demonstrate the effect of delay in expert intervention and government action. Here, we observe that it is difficult to judge the opinion of the social network user about any particular event, if experts take more time to respond and are not continuously active to make aware of the newcomers. Also, social network data become unpredictable, so this work can be helpful for the information security of social network data.The condition of existence and stability of steady states are studied. We also evaluate the Hopf bifurcation condition and calculate the critical value of delay in expert intervention. Moreover, we recognize the most sensitive parameter to the system and numerically simulate the model with some useful parameter sets to justify the theoretical findings.

Effect of Formulation Factors and Oxygen Levels on the Stability of Aqueous Injectable Solution Containing Pemetrexed.

The aim of this study was to investigate the effects of various parameters at each control strategy in drug product degradation on the stability of pemetrexed in injectable aqueous solution. A forced degradation study confirmed that oxidation is the main mechanism responsible for the degradation of pemetrexed in aqueous solutions. As control strategies, the antioxidant levels, drug concentration, pH of the control formulation, dissolved oxygen (DO) levels in the control process, and headspace oxygen levels in the control packaging were varied, and their effects on the stability of pemetrexed were evaluated. Sodium sulfite was found to be particularly effective in preventing the color change, and N-acetylcysteine (NAC) had a significant effect in preventing chemical degradation. The sulfite and NAC were found to stabilize pemetrexed in the aqueous solution by acting as sacrificial reductants. A pH below 6 caused significant degradation. The stability of pemetrexed in the solution increased as the concentration of the drug increased from 12.5 to 50 mg/mL. In addition, the DO levels in the solution were controlled by nitrogen purging, and the oxygen levels in headspace were controlled by nitrogen headspace, which also had significant positive effects in improving the stability of the pemetrexed solution; thus, it was confirmed that molecular oxygen is involved in the rate-limiting oxidation step. Based on these results obtained by observing the effects of various control strategies, the optimal formulation of an injectable solution of pemetrexed is suggested as follows: sodium sulfite at 0.06 mg/mL, as an antioxidant for prevention of color change; NAC at 1.63 mg/mL, as an antioxidant for prevention of chemical degradation; pH range 7–8; DO levels below 1 ppm; and headspace oxygen levels below 1%. In conclusion, it can be suggested that this study, which includes well-designed control strategies, can lead to a better understanding of the complex degradation mechanism of pemetrexed; thus, it can lead to the development of an injectable solution formulation of pemetrexed, with improved stability.

Modeling the effect of temperature variability on malaria control strategies

In this study, a non-autonomous (temperature dependent) and autonomous (temperature independent) models for the transmission dynamics of malaria in a population are designed and rigorously analysed. The models are used to assess the impact of temperature changes on various control strategies. The autonomous model is shown to exhibit the phenomenon of backward bifurcation, where an asymptotically-stable disease-free equilibrium (DFE) co-exists with an asymptotically-stable endemic equilibrium when the associated reproduction number is less than unity. This phenomenon is shown to arise due to the presence of imperfect vaccines and disease-induced mortality rate. Threshold quantities (such as the basic offspring number, vaccination and host type reproduction numbers) and their interpretations for the models are presented. Conditions for local asymptotic stability of the disease-free solutions are computed. Sensitivity analysis using temperature data obtained from Kwazulu Natal Province of South Africa [K. Okuneye and A.B. Gumel. Mathematical Biosciences 287 (2017) 72–92] is used to assess the parameters that have the most influence on malaria transmission. The effect of various control strategies (bed nets, adulticides and vaccination) were assessed via numerical simulations.

Gas control in TG motor region in longwall gassy mines

A number of longwall mines suffer significant gas delays due to high methane gas concentration levels (i.e. above 1.0% statutory limit for methane gas level) near the tailgate (TG) motor area of the longwall face. Therefore, in addition to development of effective goaf gas drainage and management strategies for highly gassy mines, development of face control strategies to minimize methane gas concentration levels near the tailgate motor of the longwall face is highly critical to achieve high production rates in high capacity longwall mines. To address this issue, detailed CFD models of longwall face were developed and extensive modelling simulations were carried out to investigate the effectiveness of various control options on gas concentration distribution near the tailgate motor area. To investigate the effect of mining and ventilation parameters on effectiveness of various control strategies, simulations were carried out with CFD models of Mine A. The details and results of all these studies are presented in this paper.

Mathematical model for aflatoxins risk mitigation in food

Aflatoxins (AFs) are ubiquitously found in food and animal feed. Once food is contaminated with these compounds, decontamination is often a tedious process and sometimes difficult to be achieved. Ability of probiotic microorganisms to remove AFs from various food matrices has been extensively explored. This paper proposes a mathematical model describing the mitigation process of aflatoxins by probiotics. Stability analyses of the model as well as numerical simulations were carried out to support the analytic result. The predictivity of the model indicates that the rates of formation of aflatoxin-probiotics complexes determine how fast, rigorous, and effective the mitigation of aflatoxins in a given food can be achieved. The developed model can be used to support investigations involving removal of mycotoxins in various food matrices, and to compare and contrast the effectiveness of various control strategies especially designed for decontaminating aflatoxins from food systems.

Pedestrian control measures for efficient emergency response management in mass gatherings

PurposeIn mass gatherings, a large number of people gather at a single location. To ensure safety of these people, adequate crowd management strategies are essential. Specifically, in case of an emergency, efficient evacuation can save the lives of many people. This paper aims to develop various control strategies for efficient evacuation, including providing information of routes, changing the physical layout and controlling the behavior of evacuees.Design/methodology/approachMathematical models have been developed for optimal decision-making and analysis of the effect of these control strategies during evacuation. A global search with Sequential Quadratic programming is used to increase the likelihood of obtaining the optimal solution to these models. Further, an illustrative evacuation example is presented to test the efficacy of the models.FindingsThe results of the illustrative example demonstrate that the models and their corresponding strategies can bring significant benefits for efficient evacuation.Practical implicationsThe models developed can play a significant role in helping the security staff execute evacuation better at an operational level. The authors’ models can also have implications at the strategic level for the crowd manager.Social implicationsEfficient strategies and optimal decision-making during evacuation can save lives of people. These models can develop efficient strategies that can save lives of people.Originality/valueThis paper fulfills need to study the effect of various control strategies on evacuation efficiency for a large area and its complete network.

Modeling Peste des Petits Ruminants (PPR) Disease Propagation and Control Strategies Using Memoryless State Transitions

<p><em>Peste des Petits Ruminants (PPR) is an infectious disease affecting goats and sheep. PPR has a mortality rate of 80% and a morbidity rate of 100% in naïve herds. This disease is currently of concern to Afghani goat and sheep herders as conditions in Afghanistan are conducive to the disease becoming an epidemic. PPR is similar to Rinderpest, but is not as well studied. There is a lack of empirical data on how the disease spreads or effective large-scale mitigation strategies. We developed a herd-level, event-driven model of PPR, using memoryless state transitions, to study how the virus propagates through a herd, and to identify effective control strategies for disparate herd configurations and environments. This model allows us to perform Sensitivity Analyses (SA) on environmental and disease parameters for which we do not have empirical data and to simulate the effectiveness of various control strategies. We find that reducing the amount of time from the identification of PPR in a herd to the vaccination of the herd will radically reduce the number of deaths that result from PPR. The goal of this model is to give policy makers a tool to develop effective containment strategies for managing outbreaks of PPR.</em></p>

Method for evaluating the landing aircraft sequence under disturbed conditions with the use of Petri nets

ABSTRACTOne of the important tasks that air traffic management services are faced with today is the task of maximising airport capacity. This can be achieved at the tactical level through proper organisation of air traffic around an airport. In recent years, many methods and algorithms for scheduling aircraft landings have been developed; they take into account various optimisation goals. The aim of this paper was to create a method that would allow one to evaluate landing aircraft sequences resulting from these control algorithms, especially in the presence of random disturbances. This method involves modelling the landing aircraft sequence by using Petri nets. The model and the computer tool that have been developed make it possible to take into account different kinds of disturbances and examine the effectiveness of various control strategies under these conditions. This paper presents two experiments that test disturbances with different characteristics and of different intensities. It has been shown that small but more frequent disturbances lead to the worsening of evaluation scores for a given sequence to a lesser extent than rare but larger disturbances. This is particularly important for control algorithms in which the focus is on high aircraft density. If the type of particular disturbances is properly assessed, then it will be possible to assist the decision-maker (air traffic controller) by providing him/her with quantitative evaluations of possible solutions.

Effect of culling and vaccination on bovine tuberculosis infection in a European badger (Meles meles) population by spatial simulation modelling

The control of bovine tuberculosis (bTB) in cattle herds in the Republic of Ireland (ROI) is partially hindered by spill-back infection from wild badgers (Meles meles). The aim of this study was to determine the relative effects of interventions (combinations of culling and/or vaccination) on bTB dynamics in an Irish badger population. A spatial agent-based stochastic simulation model was developed to evaluate the effect of various control strategies for bovine tuberculosis in badgers: single control strategies (culling, selective culling, vaccination, and vaccine baits), and combined strategies (Test vaccinate/cull (TVC)), split area approaches using culling and vaccination, or selective culling and vaccination, and mixed scenarios where culling was conducted for five years and followed by vaccination or by a TVC strategy. The effect of each control strategy was evaluated over a 20-year period. Badger control was simulated in 25%, 50%, and 75% area (limited area strategy) or in the entire area (100%, wide area strategy). For endemic bTB, a culling strategy was successful in eradicating bTB from the population only if applied as an area-wide strategy. However, this was achieved only by risking the extinction of the badger population. Selective culling strategies (selective culling or TVC) mitigated this negative impact on the badger population’s viability. Furthermore, both strategies (selective culling and TVC) allowed the badger population to recover gradually, in compensation for the population reduction following the initial use of removal strategies. The model predicted that vaccination can be effective in reducing bTB prevalence in badgers, when used in combination with culling strategies (i.e. TVC or other strategies). If fecundity was reduced below its natural levels (e.g. by using wildlife contraceptives), the effectiveness of vaccination strategies improved. Split-area simulations highlighted that interventions can have indirect effects (e.g. on population size) in non-treatment areas. Our model suggests that mixed control strategies could maintain infection prevalence to a low level for a considerable period even with a growing population. The model supported the hypothesis that culling strategies appeared to be the most effective method for the control of bTB in badgers using parameters, where available, from ROI, either singly or in combination with other strategies. In this model, the success of a vaccination strategy depended partially upon population density and the proportion of the population infected, therefore an initial culling program (to reduce density and/or remove infected badgers) followed by long-term vaccination may be effective in controlling bTB in badgers.

Extreme value analysis for evaluating ozone control strategies

Tropospheric ozone is one of six criteria pollutants regulated by the US EPA, and has been linked to respiratory and cardiovascular endpoints and adverse effects on vegetation and ecosystems. Regional photochemical models have been developed to study the impacts of emission reductions on ozone levels. The standard approach is to run the deterministic model under new emission levels and attribute the change in ozone concentration to the emission control strategy. However, running the deterministic model requires substantial computing time, and this approach does not provide a measure of uncertainty for the change in ozone levels. Recently, a reduced form model (RFM) has been proposed to approximate the complex model as a simple function of a few relevant inputs. In this paper, we develop a new statistical approach to make full use of the RFM to study the effects of various control strategies on the probability and magnitude of extreme ozone events. We fuse the model output with monitoring data to calibrate the RFM by modeling the conditional distribution of monitoring data given the RFM using a combination of flexible semiparametric quantile regression for the center of the distribution where data are abundant and a parametric extreme value distribution for the tail where data are sparse. Selected parameters in the conditional distribution are allowed to vary by the RFM value and the spatial location. Also, due to the simplicity of the RFM, we are able to embed the RFM in our Bayesian hierarchical framework to obtain a full posterior for the model input parameters, and propagate this uncertainty to the estimation of the effects of the control strategies. We use the new framework to evaluate three potential control strategies, and find that reducing mobile-source emissions has a larger impact than reducing point-source emissions or a combination of several emission sources.

Field transmission intensity of Schistosoma japonicum measured by basic reproduction ratio from modified Barbour’s model

BackgroundSchistosomiasis japonica, caused by infection with Schistosoma japonicum, is still recognized as a major public health problem in the Peoples’ Republic of China. Mathematical modelling of schistosomiasis transmission has been undertaken in order to assess and project the effects of various control strategies for elimination of the disease. Seasonal fluctuations in transmission may have the potential to impact on the population dynamics of schistosomiasis, yet no model of S. japonicum has considered such effects. In this paper, we characterize the transmission dynamics of S. japonicum using a modified version of Barbour’s model to account for seasonal variation (SV), and investigate the effectiveness of the control strategy adopted in Liaonan village of Xingzi county, Jiangxi Province.MethodsWe use mathematical tools for stability analysis of periodic systems and derive expressions for the basic reproduction ratio of S. japonicum in humans; we parameterise such expressions with surveillance data to investigate the conditions for persistence or elimination of the disease in the study village. We perform numerical simulations and parametric sensitivity analysis to understand local transmission conditions and compare values of the basic reproductive ratio with and without seasonal fluctuations.ResultsThe explicit formula of the basic reproduction ratio for the SV-modified Barbour’s model is derived. Results show that the value of the basic reproduction ratio, R0, of Liaonan village, Xingzi county is located between 1.064 and 1.066 (very close to 1), for schistosomiasis transmission during 2006 to 2010, after intensification of control efforts.ConclusionsOur modified version of the Barbour model to account for seasonal fluctuations in transmission has the potential to provide better estimations of infection risk than previous models. Ignoring seasonality tends to underestimate R0 values albeit only marginally. In the absence of simultaneous R0 estimations for villages not under control interventions (such villages do not currently exist in China), it is difficult to assess whether control strategies have had a substantial impact on levels of transmission, as the parasite population would still be able to maintain itself at an endemic level, highlighting the difficulties faced by elimination efforts.

BENCHMARK PROBLEMS IN STRUCTURAL ENGINEERING FOR MITIGATION OF SEISMIC VIBRATIONS

Many control algorithms and devices have been proposed over the last few decades, for protecting structures against severe dynamic loadings. However, because standard structures were not considered, direct comparison of different control strategies was not possible. To compare the results of passive, active and semi-active protective systems, and to direct future research efforts towards the most promising control strategies for alleviating dynamic responses, benchmark control problems on buildings and bridges have been developed . Thus, it becomes possible to study different aspects of the same problem in many countries, and in a coordinated fashion. By applying different control strategies to the testbed, and measuring the response to standardized loading, it is possible to directly compare the effectiveness of various control strategies. Findings of the studies can be combined in a rational manner that will result in a systematic presentation of results. The paper presents a review of the benchmark problems in structural engineering. Importance and need of benchmark problems is emphasized by presenting case studies on benchmark buildings and bridges.