R.C.A. Minnitt

45 papers receiving 262 citations

Peers

R.C.A. Minnitt
Comparison fields: 5 of 73
  • Mechanical Engineering 90
  • Building and Construction 70
  • Control and Systems Engineering 69
  • Artificial Intelligence 49
  • Environmental Engineering 41
Replace F.T. Cawood with:
F.T. Cawood South Africa
Pietro Guj Australia
Peter Buchholz Germany
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R.C.A. Minnitt relative to F.T. Cawood South Africa F.T. Cawood's profile →
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Citations per year

Countries citing papers authored by R.C.A. Minnitt

Since Specialization
Citations

This map shows the geographic impact of R.C.A. Minnitt's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by R.C.A. Minnitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R.C.A. Minnitt more than expected).

Fields of papers citing papers by R.C.A. Minnitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R.C.A. Minnitt. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by R.C.A. Minnitt. The network helps show where R.C.A. Minnitt may publish in the future.

Co-authorship network of co-authors of R.C.A. Minnitt

This figure shows the co-authorship network connecting the top 25 collaborators of R.C.A. Minnitt. A scholar is included among the top collaborators of R.C.A. Minnitt based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with R.C.A. Minnitt. R.C.A. Minnitt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 16
2 5
3 1
4 3
5
The allocation of gold production from multiple shafts feeding a common treatment plant using run-of-mine sampling of ore deliveries
2
6
An overview of sampling best practice in African mining
3
7
Cokriging for optimal mineral resource estimates in mining operations.
9
8
Sampling in the South African minerals industry.
4
9
The 'simulated chip-sample model' as a method for quantifying error and bias in sampling thin carboniferous reef types
1
10
Mechanical sampling - a manufacturer's perspective
5
11
Optimization of diesel usage at Uitvlugt Mine
6
12 1
13
Developing green energy projects in Southern Africa - a mining investment approach
1
14
Frontiers of usefulness : The economics of exhaustible resources
2
15
Part 1 : Understanding the components of the fundamental sampling error : a key to good sampling practice
13
16 9
17
Just-in-time development model for a sub-level caving underground mine in Zimbabwe.
2
18
Methodologies in the valuation of mineral rights
8
19
Input-output analysis: its potential application to the mining industry
5
20 1

About R.C.A. Minnitt

R.C.A. Minnitt is a scholar working on Fuel Technology, General Energy and Control and Systems Engineering, having authored 47 papers that have together received 296 indexed citations. Recurring topics across this work include Mining Techniques and Economics (20 papers), Mineral Processing and Grinding (17 papers) and Geochemistry and Geologic Mapping (8 papers). The work is most often cited by research in Building and Construction (70 citations), General Economics, Econometrics and Finance (37 citations) and Fuel Technology (3 citations). R.C.A. Minnitt has collaborated with scholars based in South Africa, United Kingdom and Australia. Frequent co-authors include Kim H. Esbensen, C.R. Anhaeusser, Rosemary Falcon, Simon Dominy, Clayton V. Deutsch, C. Musingwini, Francis F. Pitard, Hylke J. Glass, F.T. Cawood and Maureen Woodhall. Their work appears in journals such as Resources Policy, Ore Geology Reviews and Mathematical Geosciences.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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