The Fundamentals of Fretting Crevice Corrosion of Metallic Biomaterials for Orthopedic Implants

Metallic medical devices have been widely used in clinical applications, especially for joint arthroplasty or joint replacement surgery. Fretting corrosion, one of the most common forms of mechanically-assisted corrosion (MAC), has become a major concern associated with orthopedic medical devices. Crevice corrosion, a second mechanism of corrosion related to metallic medical devices, is a second factor of corrosion for many circumstances in medical devices that is an additional factor in the overall corrosion performance of these implants. It is a form of localized corrosion of metal surfaces present within the gap or crevice between two adjoining interfaces. The relationship and interplay between fretting and crevice corrosion is poorly understood and the observed damage seen in retrievals, which includes pitting, selective dissolution, intergranular and interphase corrosion has not been adequately duplicated in in vitro tests of mechanically assisted crevice corrosion.CoCrMo alloy, T-i6Al-4V alloy and stainless steel are the principal alloys in use today in orthopedics and are the focus of corrosion related studies. In addition, alternative materials, including ceramic materials with trusted biocompatibility, are also playing an increasingly-important role in medical device implantation. Here, we performed a series of studies intended to explore the fundamentals of fretting crevice corrosion of metallic biomaterials for orthopedic implants. We first studied CoCrMo alloy fretting corrosion debris generation and distribution using a range of characterization techniques and a custom-made fretting corrosion testing system. These several analytical surface techniques include SEM/EDS, AFM, and XPS. They were used to determine what debris was generated and to where it was distributed. Also, solution chemistry measurement (using ICP-MS) after testing was included to determine which ions and in what proportion remained in the solution. Next, a tribocorrosion model, which linked fretting mechanics, current and potential, was developed to predict currents and potential shifts resulting from fretting corrosion based on tribocorrosion theory. The model was tested against controlled fretting corrosion test conditions for its ability to predict the current-time and potential-time response. This model established a strong connection between mechanical and electrochemical aspects to demonstrate that potential and current affect each other during tribocorrosion and both are affected by other electrochemical factors (electrode area, impedance, contact mechanics, etc.) In the next step, fretting-initiated crevice corrosion in stainless steel alloys was observed and described, where fretting disruption of the surface initiated a self-sustained crevice corrosion reaction that continued even in the absence of additional fretting. The result was to comprehensively investigate fretting initiated-crevice corrosion (FICC) mechanism of stainless steel and to explore the factors, including potential and fretting duration that leads to this process. Lastly, device testing using the MTS servo-hydraulic test frame was performed to measure fretting corrosion performance of Si3N4 heads/Ti-6Al-4V modular tapers for total hip replacements in vitro and compared their behavior to standard CoCrMo heads/Ti-6Al-4V modular tapers tested under identical conditions. It was shown that using a Si3N4 ceramic head on metal trunnion significantly reduced the fretting corrosion reactions present

DEVELOPMENT OF A “2-D” TEST SYSTEM FOR VISUALIZING FRETTING CORROSION: A STUDY OF THE FRETTING CORROSION BEHAVIOR OF Co-Cr-Mo ALLOY

Fretting corrosion, one of the most common forms of mechanically-assisted corrosion (MAC), has become a major concern in orthopedic medical devices. In order to a better understand of the mechanism of fretting corrosion in orthopedic alloys and the ways to prevent implants from corroding, custom test systems need to be developed to simulate fretting corrosion in vitro and to allow visualizing of the process. This study aimed to develop a new “two dimensional” fretting crevice corrosion test system with the capacity to visualize damage progression during systematic controlled fretting corrosion processes. Another goal of the study was to experimentally verify a tribocorrosion heredity integral approach to predict abrasion-current-impedance-voltage relationships by systematic variation of fretting frequency and area. The results of Open Circuit Potential (OCP) tests, fretting current tests and visualization of fretting showed this device could achieve the basic requirement for triboelectrochemical testing and also provided direct evidence of debris generation during fretting corrosion. The fretting region was surrounded by a halo of fretting debris after removal from the solution. One possible explanation for this phenomenon could be the redeposition of fretting product. It was also found that higher fretting frequency and smaller second electrode areas lead to larger and faster voltage drops during abrasion. This is because the smaller area of the second electrode resulted in less surface area for electrons to be reduced. Higher frequency abrasion also resulted in higher film currents and faster electron generation rate which would cause more electrons accumulating at the working electrode

Evaluation of Chinese Quad-polarization Gaofen-3 SAR Wave Mode Data for Significant Wave Height Retrieval

Our work describes the accuracy of Chinese quad-polarization Gaofen-3 (GF-3) synthetic aperture radar (SAR) wave mode data for wave retrieval and provides guidance for the operational applications of GF-3 SAR. In this study, we evaluated the accuracy of the SAR-derived significant wave height (SWH) from 10,514 GF-3 SAR images with visible wave streaks acquired in wave mode by using the existing wave retrieval algorithms, e.g., the theoretical-based algorithm parameterized first-guess spectrum method (PFSM), the empirical algorithm CSAR_WAVE2 for VV-polarization, and the algorithm for quad-polarization (Q-P). The retrieved SWHs were compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field with 0.125° grids. The root mean square error (RMSE) of the SWH is 0.57 m, found using CSAR_WAVE2, and this RMSE value was less than the RMSE values for the analysis results achieved with the PFSM and Q-P algorithms. The statistical analysis also indicated that wind speed had little impact on the bias with increasing wind speed. However, the retrieval tended to overestimate when the SWH was smaller than 2.5 m and underestimate with an increasing SWH. This behavior provides a perspective of the improvement needed for the SWH retrieval algorithm using the GF-3 SAR acquired in wave mode

Fuzzy logic based energy management strategy for a fuel cell/battery/ultra-capacitor hybrid ship

In this paper, energy management strategy based on fuzzy logic is proposed for a fuel cell hybrid ship, combining proton exchange membrane fuel cell (PEMFC), battery and ultra-capacitor (UC). This hybrid system aims to optimize power distribution among each energy unit. The simulation model of the fuel cell hybrid power system is established in the MATLAB/SIMULINK simulation environment. The fuzzy logic energy strategy is verified by simulation according to the typical drive cycle of ship. The simulation results show that the proposed energy management strategy is able to satisfy power required by the ship, reduce the dynamic load of fuel cell, maintain the state of charge (SOC) of battery and SOC of the UC, and optimize the performance, fuel economy and efficiency of the hybrid systemThe research is supported by the program of the National Natural Science Foundation (No.61304186 and No.51007056)

Improved GNSS-Based Bistatic SAR Using Multi-Satellites Fusion: Analysis and Experimental Demonstration

The Global Navigation Satellite System (GNSS)-based Bistatic Synthetic Aperture Radar (SAR) is getting more and more attention in remote sensing for its all-weather and real-time global observation capability. Its low range resolution results from the narrow signal bandwidth limits in its development. The configuration difference caused by the illumination angle and movement direction of the different satellites makes it possible to improve resolution by multi-satellite fusion. However, this also introduces new problems with the resolution-enhancing efficiency and increased computation brought about by the fusion. In this paper, we aim at effectively improving the resolution of the multi-satellite fusion system. To this purpose, firstly, the Point Spread Function (PSF) of the multi-satellite fusion system is analyzed, and focusing on the relationship between the fusion resolution and the geometric configuration and the number of satellites. Numerical simulation results show that, compared with multi-satellite fusion, dual-satellite fusion is a combination with higher resolution enhancement efficiency. Secondly, a method for dual-satellite fusion imaging based on optimized satellite selection is proposed. With the greedy algorithm, the selection is divided into two steps: in the first step, according to geometry configuration, the single-satellite with the optimal 2-D resolution is selected as the reference satellite; in the second step, the angles between the azimuthal vector of the reference satellite and the azimuthal vector of the other satellites were calculated by the traversal method, the satellite corresponding to the intersection angle which is closest to 90° is selected as the auxiliary satellite. The fused image was obtained by non-coherent addition of the images generated by the reference satellite and the auxiliary satellite, respectively. Finally, the GPS L1 real orbit multi-target simulation and experimental validation were conducted, respectively. The simulation results show that the 2-D resolution of the images produced by our proposed method is globally optimal 15 times and suboptimal 8 times out of 24 data sets. The experimental results show that the 2-D resolution of our proposed method is optimal in the scene, and the area of the resolution unit is reduced by 70.1% compared to the single-satellite’s images. In the experiment, there are three navigation satellites for imaging, the time taken to the proposed method was 66.6% that of the traversal method. Simulations and experiments fully demonstrate the feasibility of the method

Traffic Flow Detection Using GNSS-R Signals

In order to detect traffic conditions effectively, a new method of traffic flow detection using GNSS-R (Global Navigation Satellite System-Reflected) signals is proposed. In this method, the direct signals and reflected signals of GNSS are received by two types of antennas respectively and collected by an universal receiver.After signal processing in a SDR(Software Defined Receiver), the correlated power of direct channel and reflected channel, and also the satellites' elevation angles can be obtained. Then vehicles can be detected by the method of dielectric constant retrieving.Test results show that vehicles in the area can be detected effectively using this method, and prove the feasibility of traffic flow detection using GNSS-R signals

A Semi-Empirical SNR Model for Soil Moisture Retrieval Using GNSS SNR Data

The Global Navigation Satellite System-Interferometry and Reflectometry (GNSS-IR) technique on soil moisture remote sensing was studied. A semi-empirical Signal-to-Noise Ratio (SNR) model was proposed as a curve-fitting model for SNR data routinely collected by a GNSS receiver. This model aims at reconstructing the direct and reflected signal from SNR data and at the same time extracting frequency and phase information that is affected by soil moisture as proposed by K. M. Larson et al. This is achieved empirically through approximating the direct and reflected signal by a second-order and fourth-order polynomial, respectively, based on the well-established SNR model. Compared with other models (K. M. Larson et al., T. Yang et al.), this model can improve the Quality of Fit (QoF) with little prior knowledge needed and can allow soil permittivity to be estimated from the reconstructed signals. In developing this model, we showed how noise affects the receiver SNR estimation and thus the model performance through simulations under the bare soil assumption. Results showed that the reconstructed signals with a grazing angle of 5°–15° were better for soil moisture retrieval. The QoF was improved by around 45%, which resulted in better estimation of the frequency and phase information. However, we found that the improvement on phase estimation could be neglected. Experimental data collected at Lamasquère, France, were also used to validate the proposed model. The results were compared with the simulation and previous works. It was found that the model could ensure good fitting quality even in the case of irregular SNR variation. Additionally, the soil moisture calculated from the reconstructed signals was about 15% closer in relation to the ground truth measurements. A deeper insight into the Larson model and the proposed model was given at this stage, which formed a possible explanation of this fact. Furthermore, frequency and phase information extracted using this model were also studied for their capability to monitor soil moisture variation. Finally, phenomena such as retrieval ambiguity and error sensitivity were stated and discussed

Evaluation of Chinese Quad-polarization Gaofen-3 SAR Wave Mode Data for Significant Wave Height Retrieval

Our work describes the accuracy of Chinese quad-polarization Gaofen-3 (GF-3) synthetic aperture radar (SAR) wave mode data for wave retrieval and provides guidance for the operational applications of GF-3 SAR. In this study, we evaluated the accuracy of the SAR-derived significant wave height (SWH) from 10,514 GF-3 SAR images with visible wave streaks acquired in wave mode by using the existing wave retrieval algorithms, e.g., the theoretical-based algorithm parameterized first-guess spectrum method (PFSM), the empirical algorithm CSAR_WAVE2 for VV-polarization, and the algorithm for quad-polarization (Q-P). The retrieved SWHs were compared with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field with 0.125° grids. The root mean square error (RMSE) of the SWH is 0.57 m, found using CSAR_WAVE2, and this RMSE value was less than the RMSE values for the analysis results achieved with the PFSM and Q-P algorithms. The statistical analysis also indicated that wind speed had little impact on the bias with increasing wind speed. However, the retrieval tended to overestimate when the SWH was smaller than 2.5 m and underestimate with an increasing SWH. This behavior provides a perspective of the improvement needed for the SWH retrieval algorithm using the GF-3 SAR acquired in wave mode

Intercomparison of Soil Moisture Retrieved from GNSS-R and from Passive L-Band Radiometry at the Valencia Anchor Station

In this paper, the SOMOSTA (Soil Moisture Monitoring Station) experiment on the intercomparison of soil moisture monitoring from Global Navigation Satellite System Reflectometry (GNSS-R) signals and passive L-band microwave radiometer observations at the Valencia Anchor Station is introduced. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and a dual-pol down-looking antenna for receiving LHCP (left-hand circular polarization) and RHCP (right-hand circular polarization) reflected signals from the soil surface. Data were collected from the three different antennas through the two channels of Oceanpal GNSS-R receiver and, in addition, calibration was performed to reduce the impact from the differing channels. Reflectivity was thus measured, and soil moisture could be retrieved. The ESA (European Space Agency)-funded ELBARA-II (ESA L Band Radiometer II) is an L-band radiometer with two channels with 11 MHz bandwidth and respective center frequencies of 1407.5 MHz and 1419.5 MHz. The ELBARAII antenna is a large dual-mode Picket horn that is 1.4 m wide, with a length of 2.7 m with −3 dB full beam width of 12° (±6° around the antenna main direction) and a gain of 23.5 dB. By comparing GNSS-R and ELBARA-II radiometer data, a high correlation was found between the LHCP reflectivity measured by GNSS-R and the horizontal/vertical reflectivity from the radiometer (with correlation coefficients ranging from 0.83 to 0.91). Neural net fitting was used for GNSS-R soil moisture inversion, and the RMSE (Root Mean Square Error) was 0.014 m3/m3. The determination coefficient between the retrieved soil moisture and in situ measurements was R2 = 0.90 for Oceanpal and R2 = 0.65 for Elbara II, and the ubRMSE (Unbiased RMSE) were 0.0128 and 0.0734 respectively. The soil moisture retrievals by both L-band remote sensing methods show good agreement with each other, and their mutual correspondence with in-situ measurements and with rainfall was also good