Rapid Fluctuations Research Articles

Research on hydration-caused thermal cracking risk of steel-concrete composite bridge pylons

Due to the large volume and different material of composite bridge pylons, a significant cracking risk has not yet been verified during concrete hydration. To clarify the hydration-caused temperature characteristics of concrete in composite pylons, based on an actual cable-stayed bridge, a 3D thermal-mechanical coupling model was established, demonstrating a good agreement between the FEM and measurements. On this basis, the temperature field and effects of pylon segments were analyzed. The key parameters influencing the temperature field, including the pouring sequences, hydration heat release, cement content, initial temperature, and convective coefficient，were analyzed. Results indicate that the temperature evolution can be divided into three stages: rapid warming, sharp cooling, and fluctuation. The temperature distributions exhibit high inside, low outside, and single-peak along the thickness direction. During the hydration process, the growth rate of the concrete elastic modulus is higher than its tensile strength. The maximum stress of concrete is 5 MPa, considerably higher than its tensile strength, leading to a significant cracking risk. Additionally, the maximum stress of the steel shell reaches 50 MPa. Adjusting the constructional parameters and environmental effects are the most effective improvement measure. The cracking risk of concrete can be reduced by 20% and 25% for every 20 kg/m3 and 50 kJ/kg reduction in the cement content and the cement heat release, respectively. Furthermore, reasonable methods for reducing unfavorable thermal effects are provided, which can facilitate the rational design and construction of composite bridge pylons.

Resilience-oriented district energy system integrated with renewable energy and multi-level seasonal energy storage

In the district energy systems (DESs), it is very essential to integrate hybrid distributed energy resources for improving energy resilience following events, and more variety of distributed resources results in a more resilient system. In this paper, the proposed district is formed by various buildings, an electric vehicle parking station, and a multi-level energy storage system. In the multi-level storage, the battery energy storage (BES) shifts energy over the hours, the pumped storage hydropower (PSH) shifts energy over the seasons, and the super-capacitor energy storage deals with rapid power fluctuations. The proposed model minimizes the energy cost by optimal scheduling of the multi-level storage system and the electric vehicles. The results demonstrate that the BES decreases the annual cost by 12 % and the coordinated BES-PSH decreases the annual energy cost by 24.3 %. The battery releases energy to the district when the electricity is expensive such as hours 13, 14, and 20. The seasonal storage shifts energy from seasons 1 and 3 to seasons 2 and 4. The uncertainty in the parameters increases the energy cost by about 40 %.

Dynamic Temperature Prediction on High-Speed Angular Contact Ball Bearings of Machine Tool Spindles Based on CNN and Informer

This study addressed the issues related to the difficulty of determining the operating status of machine tool spindle bearings due to the high rotational speeds and rapid temperature fluctuations. This paper presents an optimized model that combines Convolutional Neural Networks (CNNs) and Informer to dynamically predict the temperature rise process of bearings. Taking the H7006C angular contact ball bearing as the research object, a combination of experimental data and simulations was used to obtain the training dataset. Next, a model for predicting the temperature rise of the bearing was constructed using CNN + Informer and the structural parameters were optimized. Finally, the model’s generalization ability was then verified by predicting the bearing temperature rise process under various working conditions. The results show that the error of the simulation data source model was less than 1 °C at steady state; the temperature error of the bearing temperature rise prediction model was less than 0.5 °C at both the temperature rise and steady-state stages under variable rotational speeds and variable load conditions compared to Informer and Long Short Term Memory (LSTM) models; the maximum prediction error of the operating conditions outside the dataset was less than 0.5 °C, and the temperature rise prediction model has a high accuracy, robustness, and generalization capability.

Metal Messengers: Communication in the Bacterial World through Transition-Metal-Sensing Two-Component Systems.

Bacteria survive in highly dynamic and complex environments due, in part, to the presence of systems that allow the rapid control of gene expression in the presence of changing environmental stimuli. The crosstalk between intra- and extracellular bacterial environments is often facilitated by two-component signal transduction systems that are typically composed of a transmembrane histidine kinase and a cytosolic response regulator. Sensor histidine kinases and response regulators work in tandem with their modular domains containing highly conserved structural features to control a diverse array of genes that respond to changing environments. Bacterial two-component systems are widespread and play crucial roles in many important processes, such as motility, virulence, chemotaxis, and even transition metal homeostasis. Transition metals are essential for normal prokaryotic physiological processes, and the presence of these metal ions may also influence pathogenic virulence if their levels are appropriately controlled. To do so, bacteria use transition-metal-sensing two-component systems that bind and respond to rapid fluctuations in extracytosolic concentrations of transition metals. This perspective summarizes the structural and metal-binding features of bacterial transition-metal-sensing two-component systems and places a special emphasis on understanding how these systems are used by pathogens to establish infection in host cells and how these systems may be targeted for future therapeutic developments.

MPP Tracking with a Modified Duty Cycle Sweeping (MDCS) Algorithm for Various Environmental Irradiance Conditions

In this paper, a photovoltaic (PV) system based on modified duty cycle sweeping (MDCS) has been proposed to achieve the maximum power point tracking (MPPT). The disadvantages of perturb and observe (P&O), such as diverging tracking directions and the inability to detect the global peak during partial shading (PS), are intended to be overcome by this method (PS). An intelligent double identification and tracking method consistently tracks the global peak under partial shading and the MPP under rapid irradiance fluctuations. Strict dynamic irradiance and partial shading tests are imposed in MATLAB/Simulink@ and simulated to validate the suggested concept. Additionally, a laboratory prototype MPPT standalone PV system supported by Texas Instruments’ Code Composer Studio is operated by a SEPIC converter in conjunction with the C2000 real-time microcontroller in order to conduct an experimental validation study. The effectiveness of the method is compared with the other well-known MPPT techniques, conventional P&O. The suggested method successfully follows the global peak under various patterns of partial shading as compared to the conventional algorithms. The algorithm’s efficiency has been preserved at around 95-100%.

An archaeomagnetic intensity-based search for order in the chaos of the destruction of Hama (Syria) dated to 720 BCE

Destruction layers of ancient settlements are extremely valuable for archaeomagnetic studies as they provide a particular archaeological context allowing for the analysis of ceramic fragments strongly linked to the date of destruction. However, when examining pottery for archaeomagnetic intensity, instead of considering a snapshot in time in the geomagnetic field record, we must also consider the various dates of their initial production, which can span several decades. This introduces an unknown time interval, which is typically shorter than the temporal resolution offered by pottery typology. In this study, we obtained new archaeomagnetic intensity data using the Triaxe protocol from 16 fragments (77 specimens) of different ceramics recovered from the destruction layer of Hama (Syria) dated to 720 BCE, caused by the troops of the Assyrian King Sargon II. The selected pottery consists of serving vessels, which are generally thought to have a short lifespan, all of which were found in royal or other important buildings. Our results reveal a significant scatter, ranging from ∼65 µT to ∼81 µT (average 74.2 ± 4.2 µT). We attribute this dispersion mainly to the time interval for the production of the pottery during the 8th century BCE, a period marked by rapid intensity fluctuations according to the currently available reference geomagnetic field intensity variation curve for the Near East. Using this curve, we show that the ceramics studied had been in use for at least 30 years at the time of the city’s destruction, a surprisingly long use-life for ceramics intended for everyday use. While we acknowledge a 30-years use-life as possible, we suggest that this minimum time interval could be a result of inaccuracies in the reference intensity variation curve during the 8th century BCE. Nevertheless, our study illustrates and confirms the ability of pottery from a destruction layer to trace rapid variations in geomagnetic field intensity. Furthermore, it establishes a chronological order of production date in ceramic assemblages found in an otherwise chaotic context.

Nocturnal Turbulence at Jezero Crater as Determined From MEDA Measurements and Modeling

AbstractMars 2020 Mars Environmental Dynamics Analyzer (MEDA) instrument data acquired during half of a Martian year (Ls 13°–180°), and modeling efforts with the Mars Regional Atmospheric Modeling System (MRAMS) and the Mars Climate Database (MCD) enable the study of the seasonal evolution and variability of nocturnal atmospheric turbulence at Jezero crater. Nighttime conditions in Mars's Planetary Boundary Layer are highly stable because of strong radiative cooling that efficiently inhibits convection. However, MEDA nighttime observations of simultaneous rapid fluctuations in horizontal wind speed and air temperatures suggest the development of nighttime turbulence in Jezero crater. Mesoscale modeling with MRAMS also shows a similar pattern and enables us to investigate the origins of this turbulence and the mechanisms at play. As opposed to Gale crater, less evidence of turbulence from breaking mountain wave activity was found in Jezero during the period studied with MRAMS. On the contrary, the model suggests that nighttime turbulence at Jezero crater is explained by increasingly strong wind shear produced by the development of an atmospheric bore‐like disturbance at the nocturnal inversion interface. These atmospheric bores are produced by downslope winds from the west rim undercutting a strong low‐level jet aloft from ∼19:00 to 01:00 LTST and from ∼01:00 LTST to dawn when undercutting weak winds aloft. The enhanced wind shear leads to a reduction in the Richardson number and an onset of mechanical turbulence. Once the critical Richardson Number is reached (Ri ∼ <0.25), shear instabilities can mix warmer air aloft down to the surface.

Characterizing compensatory mechanisms in the absence of photoprotective qE in Chlamydomonas reinhardtii.

Rapid fluctuations in the quantity and quality of natural light expose photosynthetic organisms to conditions when the capacity to utilize absorbed quanta is insufficient. These conditions can result in the production of reactive oxygen species and photooxidative damage. Non-photochemical quenching (NPQ) and alternative electron transport are the two most prominent mechanisms which synergistically function to minimize the overreduction of photosystems. In the green alga Chlamydomonas reinhardtii, the stress-related light-harvesting complex (LHCSR) is a required component for the rapid induction and relaxation of NPQ in the light-harvesting antenna. Here, we use simultaneous chlorophyll fluorescence and oxygen exchange measurements to characterize the acclimation of the Chlamydomonas LHCSR-less mutant (npq4lhcsr1) to saturating light conditions. We demonstrate that, in the absence of NPQ, Chlamydomonas does not acclimate to sinusoidal light through increased light-dependent oxygen consumption. We also show that the npq4lhcsr1 mutant has an increased sink capacity downstream of PSI and this energy flow is likely facilitated by cyclic electron transport. Furthermore, we show that the timing of additions of mitochondrial inhibitors has a major influence on plastid/mitochondrial coupling experiments.

Estimation of glacier dynamics of the major glaciers of Bhutan using geospatial techniques

Abstract The purpose of this study was to determine the glacier displacement, velocity, and thickness of seven major glaciers of Bhutan and predicted potential glacier lake formation site with its depth. We named the glacier identification (ID) number 1–7 for seven glaciers. From the study, the glacier velocity between the central trunk and snout saw rapid fluctuations in 1976–1978 with an average uncertainty velocity of ± 27.10 m/year and a decreasing velocity trend. The year 2013–2014 has the lowest uncertainty in glacier velocity, with a value of ±1.24 m/year. The glacier velocity progressively increases from the snout to the main central trunk for all the glaciers with a value of 0 to 98.63 m/year. The glacier with the highest average velocity is glacier ID 5, which has a velocity of 25.58 m/year. From 2000 and 2022, all of the glaciers’ thicknesses significantly decreased from 0 to 468.2 m. The thickness of glacier ID 6 was lowered by −192.3 ± 1.99 m, making it the highest among the seven glaciers. In the future, a glacier lake is predicted to form at the base of each glacier. Glacier ID 6 is predicted to form the largest lake with a surface area of 2.572 km2 and a depth of 208.5 m.

A Robust Statistical Methodology for Measuring Enterprise Agility

In an era characterized by rapid technological advancements, economic fluctuations, and global competition, adaptability and resilience have become critical success factors for businesses navigating uncertainty and complexity. This article explores the role of enterprise agility in today’s business landscape at Latam branch of Tata Consultancy Services, where organizations face complex and diverse operations. We aim to examine how companies can become more agile in the face of emerging challenges and seize opportunities swiftly to drive growth and deliver value. Since 2014, the division has embarked on an agile transformation journey to drive growth, deliver value, foster innovation, and build resilience in an increasingly dynamic environment. We scrutinize an approach to measuring and enhancing enterprise agility, employing statistical analysis and continuous improvement methodologies to tackle real-world challenges while offering valuable insights and recommendations for organizations aiming to implement similar systems. The results of an agile transformation in a certain company’s Latam branch serve as a compelling case study, demonstrating how the implementation of targeted measures and continuous improvement can significantly bolster enterprise agility. Methodologically, our work applies a novel sequence of parametric statistical tests which, to the best of our knowledge, have not been used in the industry to validate the results of business agility metrics. In future work, we aim to create a new workflow considering non-parametric tests to address data with other statistical distributions. We conclude our work by proposing a sequence of steps for organizations to implement business agility metrics.

Topological data analysis for revealing dynamic brain reconfiguration in MEG data.

In recent years, the focus of the functional connectivity community has shifted from stationary approaches to the ones that include temporal dynamics. Especially, non-invasive electrophysiological data (magnetoencephalography/electroencephalography (MEG/EEG)) with high temporal resolution and good spatial coverage have made it possible to measure the fast alterations in the neural activity in the brain during ongoing cognition. In this article, we analyze dynamic brain reconfiguration using MEG images collected from subjects during the rest and the cognitive tasks. Our proposed topological data analysis method, called Mapper, produces biomarkers that differentiate cognitive tasks without prior spatial and temporal collapse of the data. The suggested method provides an interactive visualization of the rapid fluctuations in electrophysiological data during motor and cognitive tasks; hence, it has the potential to extract clinically relevant information at an individual level without temporal and spatial collapse.

Optimal sliding mode control for frequency stabilization of hybrid renewable energy systems

AbstractThe constant changes in the load power lead permanently to a power mismatch between the power generation and the power consumption. So, the system frequency due to the power imbalance deviates from the nominal value. Consequently, a control loop should be implemented to stabilize the system frequency whenever a load change occurs. This paper presents a new super‐twisting sliding mode control methodology for obtaining an optimal frequency performance in a multi‐pool system. The paper presents a three‐pool system for frequency deviation problems using an optimal gain Super Twisting Sliding Mode Controller (STSMC), which regulates the frequency change and the line power change to zero in a minimal time. The extent of the excellence of the study proposed is evaluated by comparing it with three Benchmark classical controllers, which are the Tilt‐Integral‐Derivative (TID), Proportional‐Integral‐Derivative (PID), and Fractional‐Order PID (FOPID). The parameters of the four controllers are determined by a proposed physical meta‐heuristic optimization technique called Transient Search Optimizer (TSO), inspired by the dynamic behaviour in the electrical circuits comprising storage elements such as capacitors and inductors during the switching actions. The system simulation is performed, and the STSMC proved overwhelming superiority over other controllers, as it deals better with the transient interval of the system response. Renewable Energy sources (RESs) like photovoltaic and wind energy systems are established, and the STSMC is tested with industrial and residential load models. Finally, energy storage devices such as batteries and superconducting magnetic energy storage are implemented to suppress the rapid fluctuations in the system response, and it succeeded in doing that as the system oscillations are greatly damped with the energy storage devices.

In Situ Monitoring of Aptamer-Protein Binding on a ZnO Surface Using Spectroscopic Ellipsometry.

The dissolution of zinc oxide is investigated using spectroscopic ellipsometry to investigate its suitability as a platform for biosensing applications. The results indicate that once the ZnO surface has been functionalised, it is suitably protected, and no significant dissolving of the ZnO occurs. The binding kinetics of the SARS-CoV-2 spike protein on aptamer-functionalised zinc oxide surfaces are subsequently investigated. Values are extracted for the refractive index and associated optical constants for both the aptamer layer used and the protein itself. It is shown that upon an initial exposure to the protein, a rapid fluctuation in the surface density is observed. After around 20 min, this effect stabilises, and a fixed increase in the surface density is observed, which itself increases as the concentration of the protein is increased. This technique and setup are demonstrated to have a limit-of-detection down to 1 nanomole (nM) and display a linear response to concentrations up to 100 nM.

Diurnal Cycle of Rapid Air Temperature Fluctuations at Jezero Crater: Probability Distributions, Exponential Tails, Scaling, and Intermittency

AbstractWe study the diurnal cycle of rapid thermal fluctuations observed by the Mars Environmental Dynamics Analyzer, onboard the Perseverance rover at Jezero Crater, as a function of local time and season. In this context, rapid refers to periods between 15 min and half a second. Some insight is also provided into wind fluctuations that are the base for most of the existing theories on turbulent flows. The results expand the observations from previous Mars missions, namely Viking, Mars Pathfinder, and Phoenix, and they add to our knowledge of near‐surface fluctuations on Mars. (a) Probability distribution functions of the fluctuations are determined and found to have exponential tails. This means that models that represent the interaction within the environment and with the surface as a stochastic forcing need to account for the sudden events responsible for the exponential tails. (b) Power density spectra are calculated and show several dynamical regimes with different slopes associated to forcing, an intermediate regime, and a higher frequency regime. All change with time of the day. The results imply that the fastest regime is not a universal scenario for the temperature fluctuations near the surface. (c) The scale dependence of the fluctuations confirms the existence of intermittent outbursts associated to the slower fluctuations, possibly associated to the larger scale structures, and explains why the spectral density slopes do not follow Kolmogorov's law. Understanding the role of larger scale structures would help refine scaling theories of the near‐surface Martian atmosphere and its interactions with the surface.

Tracking drivers’ minds: Continuous evaluation of mental load and cognitive processing in a realistic driving simulator scenario by means of the EEG

Driving safety strongly depends on the driver's mental states and attention to the driving situation. Previous studies demonstrate a clear relationship between EEG measures and mental states, such as alertness and drowsiness, but often only map their mental state for a longer period of time. In this driving simulation study, we exploit the high temporal resolution of the EEG to capture fine-grained modulations in cognitive processes occurring before and after eye activity in the form of saccades, fixations, and eye blinks. A total of 15 subjects drove through an approximately 50-km course consisting of highway, country road, and urban passages. Based on the ratio of brain oscillatory alpha and theta activity, the total distance was classified into 10-m-long sections with low, medium, and high task loads. Blink-evoked and fixation-evoked event-related potentials, spectral perturbations, and lateralizations were analyzed as neuro-cognitive correlates of cognition and attention. Depending on EEG-based estimation of task load, these measures showed distinct patterns associated with driving behavior parameters such as speed and steering acceleration and represent a temporally highly resolved image of specific cognitive processes during driving. In future applications, combinations of these EEG measures could form the basis for driver warning systems which increase overall driving safety by considering rapid fluctuations in driver's attention and mental states.

Observed Dawn and Twilight Pressure Sudden Peaks in the Global Martian Surface and Possible Relationships With Atmospheric Tides

AbstractMultilanders and rovers on Mars have observed the diurnal variation in surface pressure with two significant peaks at dawn and twilight (around 8:00 a.m. and 8:00 p.m.) at different locations near the equinox. The Dynamic Meteorology Laboratory Martian General Circulation Model (GCM) simulates similar phase‐locked surface pressure fluctuations. The surface pressure peaks at a certain local time occur at most mid‐ and low‐latitude locations, as GCM simulations suggested. By reconstructing the surface pressure variation from the horizontal mass flux obtained in the GCM simulations, we find that the pressure fluctuations are due to the diurnal variation in the horizontal wind divergence and convergence in the Martian tropical troposphere. The diurnal variation in surface pressure corresponds to the migrating diurnal tidal wind, with the enhanced convergence due to the overlap of the 4‐hr and 6‐hr tides before 8:00 a.m. and 8:00 p.m. Although the amplitudes of the 4‐hr and 6‐hr tides are smaller than those of diurnal tides, the convergences/divergences caused by the 4‐hr/6‐hr tidal winds at different altitudes are in phase and added up together to create a mass flux comparable to that induced by diurnal/semidiurnal components and lead to rapid pressure fluctuations. The 4‐hr/6‐hr tidal amplitudes and the two pressure peaks at dawn and twilight are the strongest near the equinox.

Laparoscopic adrenalectomy for adrenal tumors with endocrine activity: Perioperative management pathways for reduced complications and improved outcomes.

The major adrenal tumors with endocrine activity are primary aldosteronism, Cushing's syndrome/mild autonomous cortisol secretion, and pheochromocytoma/paraganglioma. Excessive aldosterone secretion in primary aldosteronism causes cardiovascular, renal, and other organ damage in addition to hypertension and hypokalemia. Cortisol hypersecretion in Cushing's syndrome/mild autonomous cortisol secretion causes obesity, hypertension, impaired glucose tolerance, and cardiometabolic syndrome. Massive secretion of catecholamines in pheochromocytoma/paraganglioma causes hypertension and cerebrocardiovascular disease due to rapid blood pressure fluctuation. Moreover, pheochromocytoma multi-system crisis is a feared and possibly fatal presentation of pheochromocytoma/paraganglioma. Thus, adrenal tumors with endocrine activity are considered an indication for adrenalectomy, and perioperative management is very important. They have a risk of perioperative complications, either due to direct hemodynamic effects of the hormone hypersecretion or due to hormone-related comorbidities. In the last decades, deliberate preoperative evaluation and advanced perioperative management have significantly reduced complications and improved outcomes. Furthermore, improvements in anesthesia and surgical techniques with the feasibility of laparoscopic adrenalectomy have contributed to reduced morbidity and mortality. However, there are still several challenges to be considered in the perioperative care of these patients. There are very few data available prospectively to guide clinical management, due to the rarity of adrenal tumors with endocrine activity. Therefore, most guidelines are based on retrospective data analyses or small case series. In this review, the latest knowledge is summarized, and practical pathways to reduce perioperative complications and improve outcomes in adrenal tumors with endocrine activity are presented.

Forecasting hotel room prices when entering turbulent times: a game-theoretic artificial neural network model

PurposeThis study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.Design/methodology/approachUsing three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.FindingsThe models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.Research limitations/implicationsThis study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.Practical implicationsThis study produced a reliable, accurate forecasting model considering risk and competitor behavior.Theoretical implicationsThis paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.Originality/valueThis study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.

Dynamic evolution law analysis of overburden separation and water flowing fracture under mining based on distributed optical fiber and information entropy theory

The water inrush from overburden separation is large and destructive, which is very easy to cause serious casualties and property losses. Therefore, a three-dimensional model of 150 cm × 150 cm × 60 cm (length × height × width) is established in the laboratory. And the dynamic development process of overburden separations and water flowing fractures in the process of coal mining in real time are analyzed based on distributed optical fiber and information entropy theory. The distributed optical fiber strain curve can well reflect the process and characteristics of overburden deformation and collapse. The strain curve of optical fiber shows a single peak or step shape at different mining stages. The separation position corresponds to the peak of the optical fiber strain curve or above the step. The change of strain value of optical fiber reflects the development, expansion and closure process of separation. The development height of the water flowing fractured zone corresponds to the lower part of the step of the strain curve. Strain information entropy realizes quantitative analysis of overburden system state. Strain information entropy can be divided into small amplitude rapid fluctuation period, sharp rapid adjustment period and stable slow fluctuation period. Water flowing fractures and separations are mainly produced during the period of the sharp rapid adjustment period. The height of the water flowing fractured zone and the height of the new separation increase step by step with the advance of the working face. The water flowing fractured zone finally develops to 86 cm of the model height. The highest position of the separation appears at the 112 cm height of the model. A new variable named growth rate of strain information entropy is defined, which can reflect the severity of the change of the overburden system state. When the key stratum breaks, the growth rate of strain information entropy increases significantly, which show that the key stratum plays a key role in controlling the overburden deformation process. In addition, the optical fiber strain curve can also reflect important information such as the change of advance support pressure, the distribution state of gangue in goaf and the breaking characteristics of key strata.

Environmental impact of water exchange blocking in a strait – a multidisciplinary study in the Baltic Sea

In this study, we report the environmental impact of water exchange blocking by a 3 km road dam built in 1896 in the shallow Väike Strait, north-eastern Baltic Sea. Using a multidisciplinary measurement campaign and numerical simulations, we show ecological conditions in the strait have considerably altered; the previously free-flowing strait now comprises two bays with separate circulation systems. Water exchange in the area close to the dam has decreased 10–12-fold. Since advection is weakened, exchange with the atmosphere and sediments has a relatively greater role in shaping water characteristics. Consequently, occasional very high sea surface temperature, salinity, and total nitrogen, and strong diurnal cycles in water temperature (>4°C) and dissolved oxygen (>4 mg l−1) were observed near the dam in summer. Oxygen levels are continuously below saturation in winter and concentration occasionally drops to hypoxic levels with ice cover. Nitrogen content in sediments near the dam is 3–4 times higher than in neighboring areas. The dam also modifies sea level, wind wave and suspended matter patterns in the strait. Sediments near the dam show elevated content of hazardous substances likely associated with traffic on the dam road. The phytobenthos community near the dam is dominated by annual green algae, which massively decompose during winter. The dam likely impedes fish migration between suitable feeding and spawning areas, also there have been fish kills caused by rapid fluctuations in sea levels, amplified by dam. The construction of new openings would alleviate negative impacts of the dam.