Department of Mining and Minerals Engineering

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Acid Leaching of Rare Earth Elements from Coal and Coal Ash: Implications for Using Fluidized Bed Combustion To Assist in the Recovery of Critical Materials
Honaker, Rick; Zhang, Wencai; Werner, Joshua (American Chemical Society, 2019-07-18)
High temperature pretreatment of coal-based mineral matter in an oxidizing environment significantly enhances the leaching characteristics of rare earth elements (REEs). A research study has found that the temperatures used in fluidized-bed combustion (FBC) of coal to produce electricity are near optimum for pre-treating the associated mineral matter prior to leaching to maximize the recovery of critical materials. Tests were performed on representative samples collected from preparation plants treating West Kentucky No. 13, Illinois No. 6, and Fire Clay coal seam sources as well as fly ash and bed ash samples from two FBC power plants. Acid leaching tests using 1.2M HCl at 75℃ were performed on both the coal and the FBC ash samples. Prior to leaching, the coal samples were pretreated at temperatures of 600℃, 750℃, and 900℃ in an oxidizing environment to study the effect on leaching characteristics. The results showed that pretreatment at 600℃ for 2 hours resulted in a significant increase in REE recovery from a range of 20-40% to about 80% for all coal sources. The leaching kinetics are characterized by a quick release of rare earth elements within the first few minutes of the process. For the West Kentucky No. 13 coal source, about 75% of REEs were leached in the first 15 min from the 1.4-1.8 specific gravity (SG) fraction that was calcined at 600℃. Additionally, the leaching kinetics of the major contaminant, i.e., Fe, were much lower than the REEs, which significantly benefits the efficiency of leaching and the downstream upgrading processes. REE leaching characteristics of the FBC ash samples were similar to that of the calcined coals. Mineralogy characterization showed that the degree of crystallinity for both the calcined coal and FBC samples were similar to the original associated mineral matter, which provided evidence for the advantage of using the FBC by- products as REE feedstocks over pulverized coal boilers that utilize temperatures greater than 1200℃. These findings were used to develop a conceptual flowsheet that incorporates FBC technology and its typical combustion environment to enhance the feasibility of recovering critical materials from coal-based sources.
Advancing respirable coal mine dust source apportionment: a preliminary laboratory exploration of optical microscopy as a novel monitoring tool
Santa, Nestor; Sarver, Emily A. (2024-04-16)
Exposure to respirable coal mine dust (RCMD) can cause chronic and debilitating lung diseases. Real-time monitoring capabilities are sought which can enable a better understanding of dust components and sources. In many underground mines, RCMD includes three primary components which can be loosely associated with three major dust sources: coal dust from the coal seam itself, silicates from the surrounding rock strata, and carbonates from the inert ‘rock dust’ products that are applied to mitigate explosion hazards. A monitor which can reliably partition RCMD between these three components could thus allow source apportionment. And tracking silicates, specifically, could be valuable since the most serious health risks are typically associated with this component-particularly if abundant in crystalline silica. Envisioning a monitoring concept based on field microscopy, and following up on prior research using polarized light, the aim of the current study was to build and test a model to classify respirable-sized particles as either coal, silicates, or carbonates. For model development, composite dust samples were generated in the laboratory by successively depositing dust from high-purity materials onto a sticky transparent substrate, and imaging after each deposition event such that the identity of each particle was known a priori. Model testing followed a similar approach, except that real geologic materials were used as the source for each dust component. Results showed that the model had an overall accuracy of 86.5%, indicating that a field-microscopy based monitor could support RCMD source apportionment and silicates tracking in some coal mines.
Apparatus for improved ash and sulfur rejection
(United States Patent and Trademark Office, 1996-06-04)
An apparatus for separating impurities from coal, includes a device for removing a predetermined amount of ash-forming substances from the coal and a device for removing a predetermined amount of high specific gravity (e.g., pyrite) from the coal having been processed by the ash-forming substance removing device. The ash-forming substance removing device and the high specific gravity material removing device each possess characteristics that allow them to more efficiently reject different types of mineral impurities from coal.
Application of Double-Difference Seismic Tomography to Carbon Sequestration Monitoring at the Aneth Oil Field, Utah
Slaker, Brent; Westman, Erik C.; Luxbacher, Kramer Davis; Ripepi, Nino (MDPI, 2013-10-23)
Double difference seismic tomography was performed using travel time data from a carbon sequestration site at the Aneth oil field in southeast Utah as part of a Department of Energy initiative on monitoring, verification, and accounting (MVA) of sequestered CO2. A total of 1211 seismic events were recorded from a borehole array consisting of 23 geophones. Artificial velocity models were created to determine the likelihood of detecting a CO2 plume with an unfavorable event and receiver arrangement. In tests involving artificially modeled ray paths through a velocity model, ideal event and receiver arrangements clearly show velocity reductions. When incorporating the unfavorable event and station locations from the Aneth Unit into synthetic models, the ability to detect velocity reductions is greatly diminished. Using the actual, recorded travel times, the Aneth Unit results show differences between a synthetic baseline model and the travel times obtained in the field, but the differences do not clearly indicate a region of injected CO2. MVA accuracy and precision may be improved through the use of a receiver array that provides more comprehensive ray path coverage, and a more detailed baseline velocity model.
Characteristics of respirable dust in eight Appalachian coal mines: A dataset including particle size and mineralogy distributions, and metal and trace element mass concentrations
Sarver, Emily A.; Keles, Cigdem; Rezaee, Mohammad (Elsevier, 2019-08-01)
Respirable dust samples were collected in several key locations of eight underground coal mines in central and northern Appalachia. In total, there were 76 unique sampling events (i.e., specific location in a specific mine). Here, we present data from each event describing particle size and mineralogy class distributions across the ∼100–10,000nm size range, which were determined using SEM-EDX; and estimated mass concentrations of potentially bioaccessible and total acid-soluble metals and trace elements, which were determined using sequential digestions with digestate analysis by ICP-MS. Discussion of this dataset is included in a companion research article “Beyond conventional metrics: Comprehensive characterization of respirable coal mine dust” Sarver et al., 2019.
Characterization of Particulates from Australian Underground Coal Mines
LaBranche, Nikky; Keles, Cigdem; Sarver, Emily A.; Johnstone, Kelly; Cliff, David (MDPI, 2021-04-23)
The re-identification of coal workers’ pneumoconiosis in Queensland in 2015 has prompted improvements in exposure monitoring and health surveillance in Australia. The potential consequences of excessive exposure to respirable dust may depend upon the size, shape and mineralogical classes of the dust. Technology has now advanced to the point that the dust characteristics can be explored in detail. This research collected respirable dust samples from four operating underground coal mines in Australia for characterization analysis using scanning electron microscopy (SEM) with energy dispersive X-ray (EDX). The research found multiple mineralogical classes present with their own particle size distributions. The variation between mines appears to have had a larger effect on particle size distribution than the differences in mining processes within individual mines. This may be due to variations in the geologic conditions, seam variation or mining conditions.
Cleaning and dewatering fine coal
(United States Patent and Trademark Office, 2017-10-17)
Fine coal is cleaned of its mineral matter impurities and dewatered by mixing the aqueous slurry containing both with a hydrophobic liquid, subjecting the mixture to a phase separation. The resulting hydrophobic liquid phase contains coal particles free of surface moisture and droplets of water stabilized by coal particles, while the aqueous phase contains the mineral matter. By separating the entrained water droplets from the coal particles mechanically, a clean coal product of substantially reduced mineral matter and moisture contents is obtained. The spent hydrophobic liquid is separated from the clean coal product and recycled. The process can also be used to separate one type of hydrophilic particles from another by selectively hydrophobizing one.
Comparison of respirable coal mine dust constituents estimated using FTIR, TGA, and SEM-EDX
Pokhrel, Nishan; Agioutanti, el E.; Keles, Cigdem; Afrouz, Setareh; Sarver, Emily A. (Springer, 2022-02-24)
Since the mid-1990s, there has been a resurgence of severe lung disease among US coal miners. This has prompted efforts to better characterize and monitor respirable dust exposures—especially with respect to mineral constituents sourced from rock strata surrounding the coal, which is believed to play a central role in many cases of disease. Recently, a rapid analysis method for silica (quartz) mass has been developed using direct-on-filter Fourier transform infrared (FTIR) spectroscopy. It can concurrently provide an estimate of kaolinite, presumably a primary silicate mineral in many coal mines. Other methods, including thermogravimetric analysis (TGA) and scanning electron microscopy with energy-dispersive X-ray (SEM–EDX), can also be used to estimate respirable coal mine dust constituents. However, there have been few efforts to compare results across multiple methods. Here, FTIR, TGA, and SEM–EDX were used to analyze 93 sets of respirable dust samples collected in 16 underground coal mines across the USA.
A Comprehensive Review of Rare Earth Elements Recovery from Coal-Related Materials
Zhang, Wencai; Noble, Christopher Aaron; Yang, Xinbo; Honaker, Rick (MDPI, 2020-05-17)
Many studies have been published in recent years focusing on the recovery of rare earth elements (REEs) from coal-related materials, including coal, coal refuse, coal mine drainage, and coal combustion byproducts particularly fly ash. The scientific basis and technology development have been supported by coal geologists and extractive metallurgists, and through these efforts, the concept has progressed from feasibility assessment to pilot-scale production over the last five years. Physical beneficiation, acid leaching, ion-exchange leaching, bio-leaching, thermal treatment, alkali treatment, solvent extraction, and other recovery technologies have been evaluated with varying degrees of success depending on the feedstock properties. In general, physical beneficiation can be a suitable low-cost option for preliminary upgrading; however, most studies showed exceedingly low recovery values unless ultrafine grinding was first performed. This finding is largely attributed to the combination of small RE-bearing mineral particle size and complex REE mineralogy in coal-based resources. Alternatively, direct chemical extraction by acid was able to produce moderate recovery values, and the inclusion of leaching additives, alkaline pretreatment, and/or thermal pretreatment considerably improved the process performance. The studies reviewed in this article revealed two major pilot plants where these processes have been successfully deployed along with suitable solution purification technologies to continuously produce high-grade mixed rare earth products (as high as +95%) from coal-based resources. This article presents a systematic review of the recovery methods, testing outcomes, and separation mechanisms that are involved in REE extraction from coal-related materials. The most recent findings regarding the modes of occurrence of REEs in coal-related materials are also included.
A Computer-Controlled SEM-EDX Routine for Characterizing Respirable Coal Mine Dust
Johann-Essex, Victoria; Keles, Cigdem; Sarver, Emily A. (MDPI, 2017-01-23)
A recent resurgence in coal workers’ pneumoconiosis (or “black lung”) and concerns over other related respiratory illnesses have highlighted the need to elucidate characteristics of airborne particulates in occupational environments. A better understanding of particle size, aspect ratio, or chemical composition may offer new insights regarding causal factors of such illnesses. Scanning electron microscopy analysis using energy dispersive X-ray (SEM-EDX) can be used to estimate these particle characteristics. If conducted manually, such work can be very time intensive, limiting the number of particles that can be analyzed. Moreover, potential exists for user bias in interpretation of EDX spectra. A computer-controlled (CC) routine, on the other hand, can allow similar analysis at a much faster rate, increasing total particle counts and reproducibility of results. This paper describes a CCSEM-EDX routine specifically developed for analysis of respirable dust samples from coal mines. The routine is verified based on reliability of results obtained on samples of known materials, and reproducibility of results obtained on a set of 10 dust samples collected in the field. The characteristics of the field samples are also discussed with respect to mine occupational environments.
A conceptual protocol for integrating multiple parameters for risk assessment due to induced seismicity in a deep mine
Ghaychi Afrouz, Setareh; Westman, Erik C.; Dehn, K. K.; Weston, B.; Luxbacher, Kramer Davis (2020-01-01)
Typically, the time-dependent b-value has been shown to decrease prior to the occurrence of a higher-magnitude event, thus providing a possible indicator of the timing of a significant event. The Energy Index relates seismic energy to seismic moment and an increase in the Energy Index has been associated with an increase in rock mass stress levels. The distribution of P-wave velocity also indicates rock mass stress levels and is provided from time-lapse passive seismic tomography. Finally, prior studies have correlated an increased production rate (blast rate) to higher stress concentrations, potentially triggering a seismic event. Therefore, Energy Index, P-wave velocity, and blast rate may be correlated to stress levels within the rock mass and may imply the magnitude and timing of an event. In this case study, these parameters are used in a back analysis to define a safety protocol for a deep, narrow-vein, underground mine. A catalog of b-value, Energy Index, P-wave velocity, and mine excavation blasting rate, was developed and integrated as a concept of hazardous thresholds. The combination of these various parameters can be helpful in determining the potential for high-risk times and locations due to induced stress.
Considerations for an Automated SEM-EDX Routine for Characterizing Respirable Coal Mine Dust
Johann, Victoria Anne; Sarver, Emily A. (2015)
Respirable dust in coal mining environments has long been a concern for occupational health. Over the past several decades, much effort has been devoted to reducing dust exposures in these environments, and rates of coal workers’ pneumoconiosis (CWP) have dropped significantly. However, in some regions, including parts of Central Appalachia it appears that incidence of CWP has recently been on the rise. This trend is yet unexplained, but a possible factor might be changes in specific dust characteristics, such as particle composition, size or shape. Prior work in our research group has developed a standardized methodology for analyzing coal mine dust particles on polycarbonate filter media using scanning electron microscopy with energy dispersive x-ray (SEM-EDX). While the method allows individual particles to be characterized, it is very time-intensive because the instrument user must interrogate each particle manually; this limits the number of particles that can practically be characterized per sample. Moreover, results may be somewhat user-dependent since classification of particle composition involves some interpretation of EDX spectra. To overcome these problems, we aim to automate the current SEM-EDX method. The ability to analyze more particles without user bias should increase reproducibility of results as well as statistical confidence (i.e., in applying characteristics of the analyzed particles to the entire dust sample.) Some challenges do exist in creating an automated routine, which are primarily related to ensuring that the available software is programmed to differentiate individual particles from anomalies on the sample filter media, select and measure an appropriate number of particles across a sufficient surface area of the filter, and classify particle compositions similarly to a trained SEM-EDX user following a manual method. This paper discusses the benefits and challenges of an automated routine for coal mine dust characterization, and progress to date toward this effort.
Considerations for TGA of Respirable Coal Mine Dust Samples
Scaggs, Meredith; Sarver, Emily A.; Keles, Cigdem (2015)
Respirable dust in coal mining environments has long been a concern for occupational health. Over the past several decades, much effort has been devoted to reducing dust exposures in these environments, and rates of coal workers’ pneumoconiosis (CWP) have dropped significantly. However, in some regions, including parts of Central Appalachia it appears that incidence of CWP has recently been on the rise. This trend is yet unexplained, but a possible factor might be changes in specific dust characteristics, such as particle composition, size or shape. Prior work in our research group has developed a standardized methodology for analyzing coal mine dust particles on polycarbonate filter media using scanning electron microscopy with energy dispersive x-ray (SEM-EDX). While the method allows individual particles to be characterized, it is very time-intensive because the instrument user must interrogate each particle manually; this limits the number of particles that can practically be characterized per sample. Moreover, results may be somewhat user-dependent since classification of particle composition involves some interpretation of EDX spectra. Respirable dust in underground coal mines has long been associated with occupational Jung diseases, particularly coal workers' pneumoconiosis (CWP) and silicosis. Regular dust sampling is required for assessing occupational exposures , and compliance with federal regulations is determined! on the basis of total respirable dust concentration and crystalline silica content by mass. In light of continued incidence of CWP amongst coal miners, additional information is needed to determine what role specific dust characteristics might play in health outcomes . While particle-level analysis is ideal, current time requirements and costs make this simply unfeasible for large numbers of samples. However, opportunities do exist for gleaning additional information from bulk analysis (i.e., beyond total mass and silica content) using relatively quick and inexpensive methods. Thermogravimetric analysis (TGA) may be a particularly attractive option. It involves precise sample weight measurement in a temperature controlled environment, such that weight changes over specific temperature ranges can be correlated to cheruical changes of particular sample constituents. In principle, TGA offers the ability to determine the coal and total mineral mass fractions in respirable dust samples. Such analysis could conceivably be combined with standard methods currently used to measure total mass and silica content. Under some circumstances , TGA might also be extended to provide information on specific dust constituents of interest (such as calcite). In this paper, we consider the benefits and challenges of TGA of respirable coal mine dust samples, and provide preliminary results and observations from ongoing research on this topic.
Data Analyses of Quarry Operations and Maintenance Schedules: A Production Optimization Study
George, Brennan; Nojabaei, Bahareh (MDPI, 2023-06-15)
In this research, data analytics and machine learning were used to identify the performance metrics of loaders and haul trucks during mining operations. We used real-time collected data from loaders and haul trucks operating in multiple quarries to broaden the scope of the study and remove bias. Our model indicates relationships between multiple variables and their impacts on production in an operation. Data analysis was also applied to ground engagement tools (GET) to identify key preventative maintenance schedules to minimize production impact from capital equipment downtime. Through analysis of the loader’s data, it was found there is an efficient cycle time of around 35 s to 40 s, which yielded a higher payload. The decision tree classifier algorithm created a model that was 87.99% accurate in estimating the performance of a loader based on a full analysis of the data. Based on the distribution of production variables across each type of loader performing in a similar work environment, the Caterpillar 992K and 990K were the highest-yielding machines. Production efficiency was compared before and after maintenance periods of ground engaging tools on loader buckets. With the use of maintenance and production records for these tools, it was concluded that there was no distinguishable change in average production and percentage change in production value before and after maintenance days.
Demonstration of Optical Microscopy and Image Processing to Classify Respirable Coal Mine Dust Particles
Santa, Nestor; Keles, Cigdem; Saylor, J. R.; Sarver, Emily A. (MDPI, 2021-08-02)
Respirable coal mine dust represents a serious health hazard for miners. Monitoring methods are needed that enable fractionation of dust into its primary components, and that do so in real time. Near the production face, a simple capability to monitor the coal versus mineral dust fractions would be highly valuable for tracking changes in dust sources—and supporting timely responses in terms of dust controls or other interventions to reduce exposures. In this work, the premise of dust monitoring with polarized light microscopy was explored. Using images of coal and representative mineral particles (kaolinite, crystalline silica, and limestone rock dust), a model was built to exploit birefringence of the mineral particles and effectively separate them from the coal. The model showed >95% accuracy on a test dataset with known particles. For composite samples containing both coal and minerals, the model also showed a very good agreement with results from the scanning electron microscopy classification, which was used as a reference method. Results could further the concept of a “cell phone microscope” type monitor for semi-continuous measurements in coal mines.
Design of Cell-Based Flotation Circuits under Uncertainty: A Techno-Economic Stochastic Optimization
Amini, Seyed Hassan; Noble, Christopher Aaron (MDPI, 2021-04-27)
The design of cell-based flotation circuits is often completed in two distinct phases, namely circuit structure identification and equipment sizing selection. While recent literature studies have begun to address the implications of stochastic analysis, industrial practice in flotation circuit design still strongly favors the use of deterministic metallurgical modeling approaches. Due to the complexity of the available mathematical models, most flotation circuit design techniques are constructed based on deterministic models. Neglecting the impact of various sources of uncertainty may result in the identification of circuit solutions that are only optimal in a narrow region of specific operating scenarios. One promising strategy to address this shortcoming is through the Sample Average Approximation (SAA) methodology, a stochastic approach to handling uncertainty that has been widely applied in other disciplines such as supply chain and facility location management problems. In this study, a techno-economic optimization algorithm was formulated to select the optimal size and number of flotation cells for a fixed circuit structure while considering potential uncertainty in several input parameter including feed grade, kinetic coefficients, and metal price. Initially, a sensitivity analysis was conducted to screen the uncertain parameters. After simplifying the optimization problem, the SAA approach was implemented to determine the equipment configuration (i.e., cell size and number) that maximizes the plant’s net present value while considering the range of potential input values due to parameter uncertainty. The SAA methodology was found to be useful in analyzing uncertainty in flotation kinetics; however, the approach did not provide a useful means to assess the influence of uncertainties in ore grade and metal price, as these values are not significant in determining equipment size but rather influence the optimal circuit structure, which was not considered in this study. Results from an application example indicate that the SAA approach produces optimal solutions not initially identified in a deterministic optimization, and these SAA solutions tend to provide greater robustness to uncertainty and variation in the flotation kinetics.
Determination of critical parameters in the analysis of road tunnel fires
Haghighat, Alireza; Luxbacher, Kramer Davis (Elsevier, 2018-07-12)
The analysis of the fluid characteristics downstream of a fire source in transportation tunnels is one the most important factor in the emergency response, evacuation, and the rescue service studies. Some crucial parameters can affect the fluid characteristics downstream of the fire. This research develops a statistical analysis on the computational fluid dynamics (CFD) data of the road tunnel fire simulations in order to quantify the significance of tunnel dimensions, inlet air velocity, heat release rate, and the physical fire size (fire perimeter) on the fluid characteristics downstream of the fire source. The selected characteristics of the fluid (response variables) were the average temperature, the average density, the average viscosity, and the average velocity. The prediction of the designed statistical models was assessed; then the significant parameters’ effects and the parameters interactive effects on different response variables were determined individually. Next, the effect of computational domain length on the selection of the significant parameters downstream of the fire source was analyzed. In this statistical analysis, the linear models were found to provide the statistically good prediction. The effect of the fire perimeter and the parameters interactive effects on the selected response variables downstream of the fire, were found to be insignificant. © 2018
Determining Coalbed Methane Production and Composition from Individual Stacked Coal Seams in a Multi-Zone Completed Gas Well
Ripepi, Nino; Louk, Kyle; Amante, Joseph; Schlosser, Charlies; Tang, Xu; Gilliland, Ellen (MDPI, 2017-10-02)
This work proposes a novel and cost-effective approach to determine coalbed methane (CBM) production and composition from individual coal seams in a multi-zone completed CBM well. The novel method uses water to cover individual coal seams in a low pressure CBM well followed by an Echometer fluid level survey to determine the water level. Corresponding gas flow measurements and natural gas chromatography analysis are used to determine gas production and composition from unique zones. A field test using this technology is conducted in Central Appalachia for a multi-zone CBM well containing 18 coal seams. Test results show that the shallow coal seams contribute the majority of the total CBM production in this multi-zone well, and the deeper coal seams contain more heavy hydrocarbons like ethane and propane.
Development of a Methodology for Interface Boundary Selection in the Multiscale Road Tunnel Fire Simulations
Haghighat, Alireza; Luxbacher, Kramer Davis; Lattimer, Brian Y. (2018-07)
The simulation of large complex dynamical systems such as a fire in road tunnels is necessary but costly. Therefore, there is a crucial need to design efficient models. Coupling of computational fluid dynamics (CFD) models and 1D network modeling simulations of a fire event, a multiscale method, can be a useful tool to increase the computational efficiency while the accuracy of simulations is maintained. The boundary between a CFD model (near field) and a 1D model (far field) plays a key role in the accuracy of simulations of large systems. The research presented in this paper develops a novel methodology to select the interface boundary between the 3D CFD model and a 1D model in the multiscale simulation of vehicle fire events in a tunnel. The development of the methodology is based on the physics of the fluid structure, turbulent kinetic energy of the dynamical system, and the vortex dynamics. The methodology was applied to a tunnel with 73.73 m(2) cross section and 960 m in length. Three different vehicle fire scenarios were investigated based on two different heat reslease rates (10 MW and 30 MW) and two different inlet velocities (1.5 m/s and 5 m/s). all parameters upstream and downstream of the fire source in all scenarios were investigated at t = 900 s. The effect of changes in heat release rate (HRR) and air velocity on the selection of an interface boundary was investigated. The ratio between maximum longitudinal and transversal velocities was within a range of 10 to 20 in the quasi-1D region downstream of the fire source. The selected downstream interface boundary was 12D(h) m downstream of the fire for the simulations. The upstream interface boundary was selected at 0.5 D-h m upstream the tip of the object when the velocity was greater than equal to the V-c. In the simulations with backlayering (V < V-c), the interface boundary was selected 10 m further from the tip of the backlayering (1.2 D-h). An indirect coupling strategy was utilized to couple CFD models to 1D models at the selected interface boundary; then, the coupled models results were compared to the full CFD model results. The calculated error between CFD and coupled models for mean temperature and velocity at different cross sections were calculated at less than 5%. The findings were used to recommend a modification to the selection of interface boundary in multiscale fire simulations in the road tunnels and more complex geometries such as mines.
Differential Entropy Analysis of the Acoustic Characteristics of a Biomimetic Dynamic Sonar Emitter
Yang, Luhui; Müller, Rolf (MDPI, 2020-03-03)
Active noseleaf deformations during pulse emission observed in hipposiderid and rhinolophid bats have been shown to add a time dimension to the bats’ acoustic emission characteristics beyond the established dependencies on frequency and direction. In this study, a dense three-dimensional acoustic characteristics were obtained by the time series of smoothed signal amplitudes at different directions and frequencies collected by a biomimetic dynamic sonar emitter. These data have been analyzed using differential entropy which was used as a measure to compare the encoding capacity for sensory information between the three different dimensions. The capacity for sensory information encoding measured in this way along time dimension was found to be similar to that along the frequency dimension. But both of them provided less information than provided by the direction dimension.

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