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By Mario A. Morin

Mine design, planning and scheduling is a very complex, iterative process comprising several interrelated and interdependent activities. Understanding how this process works, identifying the critical pieces of information and the decisions to be made is key to initiating business process improvements (BPI) or business process reengineering (BPR) activities. Fundamental to most BPI and BPR work is some form of systems analysis. Structured Analysis is a powerful systems analysis technique that is well suited for modeling and analyzing complex process activities. Through a series of diagrams, this paper presents a vertical slice through the analysis work performed for formally describing the underground hardrock mine design and planning process. These diagrams illustrate how simple graphic constructs can be used to decompose the most complex situations into easily understandable diagrams that facilitate understanding, communication, improvement and reengineering.

May 1, 2002

By J. M. Applegate, C. L. Morgan

Introduction In the same way that a blueprint communicates informa¬tion about a structure, a systems architecture should provide information that guides the construction and implementation of a computing system. Taking the blueprint analogy a step further, a plot plan can also show where, in the "bigger picture," a particular design fits (if in fact it does) and what a builder needs to know about the environment in which he or she will operate. In the context of business systems, a meaningful architecture should convey the following: • the primary purpose of computer-based systems rela¬tive to particular tasks or operations, • the relationship of the systems to each other and an indication of their interaction and dependencies, • the relationship of the systems relative to the organiza¬tion and its objectives, • indications of where IS/IT resources can best be allo¬cated to support the organization and • the overall context in which new systems and technolo¬gies can be assessed for both their impacts on current systems and on the organization itself. In theory, a well-designed systems architecture should allow an organization to focus its resources on those aspects of its business that matter most, thus, leveraging investments in information technology to a competitive advantage. In addition, the way that a computing systems architecture is represented should be un¬derstandable to non-IT staff, and it should be eas¬ily recognized by the people it supports. This pa¬per attempts to show that a meaningful systems model exists and that its applica¬tion to mining can achieve the desired results. The following discus¬sion is based on the au¬thors interpretation of a concept referred to as the computer integrated manu¬acturing (CIM) model, as developed by Allen-Bradley. An inherent strength of the CIM approach is that the model combines aspects of business-reporting structures with the manufacturing process itself. What results is a systems frame¬work that is aligned with relevant business processes and is, therefore, easier for non-IS/IT personnel to interpret. The successful application of the CIM model can be seen in a large number of both discrete and process-manufacturing facilities throughout the United States. This paper provides a brief overview of the CIM model and then describes how the model can be applied at a conceptual level to the mining industry. Finally, this paper proposes an extension to the CIM model that the authors believe will make it easier to understand and apply. CIM model As shown on Fig. 1, the CIM model begins with the most detailed levels of process equipment and works its way up to the highest level of consolidated financial reporting. Systems at each level are characterized by common attributes, users, time frames, etc., providing a clear picture of their interac¬tion. Further analysis of the relationships between systems and between levels provides insight into the opportunities for integration. Regardless of the industry or processes involved, the CIM model provides a framework in which the characteristics of systems and the data they manage can be predicted based on the nature of the business function they support. In general, as data moves upward from the lower rungs of the CIM model, it changes from de¬scribing the physical na¬ture of a process to describ¬ing its financial aspects (e.g., from productivity to cost). The time frame to which data applies also transitions from a very short duration, perhaps only milliseconds, to financial or regulatory reporting time frames that may span years. In a simi¬

Jan 1, 2000

By C. West

Structured or embossed HDPE and LLDPE geomembranes have been available to mine owners and designers for over ten (10) years. As many owners and designers discover and demand the consistent high quality characteristics of this type of geomembrane due to the unique manufacturing process, the use of these materials in new mines, mine expansions and final closure designs has steadily increased. Structured liner materials are available for double lined and final cover systems and are revolutionizing the way ponds, pads and final closures are constructed. This paper will discuss the structured or embossed geomembrane concept and manufacturing process. Additionally, the paper will present comparative testing illustrating the major advantages of using this type of product in these types of applications. Both technical and economic advantages are illustrated. The cost savings include lower installation costs, less material used, and third party inspection times not to mention better performance. These new systems will be presented.

Jan 1, 2011

A study of literature on the epidiorite dykes which transgress the Broken Hill lode and its wall rocks reveals a considerable diversity of thought regarding the time of emplacement of such dykes. In this paper it is deduced that the epidiorite dykes were formed at a late stage and were probably post-ore. Detailed mapping, sampling, and correlation of data from over 100 exposures substantiates this deduction. Physical disruption of the epidiorite dykes is indicated and some interaction of the epidiorite and ore at the time of intrusion is inferred.Further petrological study may confirm this.

Jan 1, 1968

By Lim Thi Duong, Du Duy Bui, Thuat Ngoc Pham, Chuc Ngoc Pham, Que Anh Nguyen, Hoa Anh Bui, Chi Thi Ha Nguyen, Hoan Thanh Nguyen, Bac Quang Nguyen, Kien Trung Nguyen, Dung Trung Doan, Nhiem Ngoc Dao

The microstructures and kinetics of a rich iron ore ( TFe = 65.84%) of Na Rua mine, Vietnam, used for the iron production were investigated in this study. Thermal behaviors of iron ores were well-examined by heating microscopy, thermogravimetric analysis, and differential thermal analysis. After being pelletized and then oxidatively fired at 500–1200 °C for 2 h, the pellets fired at 1200 °C (P1200) displayed a hard and dense structure with a decent compressive strength of 317.9 kg/pellet whereas those fired at 500 °C (P500) had a soft and spongy structure. The reduction of iron pellets conducted in a flow of a 60–100% CO2/ Ar gas mixture at 900–1100 °C showed significantly higher efficiency than the reduction using coal. The spongy pellets showed superior performance for the reduction in the CO/Ar gas mixture compared to the dense ones, compatible with the production of sponge iron. When mixed with an amount of coal, P1200 designed for iron production in the blast furnace demonstrated an impressive reduction activity compared to P500 and previous studies. The kinetics of pellet reduction was determined by the diffusion of substances through the solid product layers having the mathematical model of 1 − 2 3 f − (1 − f )2∕3 = kt . The microstructures of pellets during the oxidative firing and reduction were also examined by X-ray diffractometry; scanning electronic microscopy; energy-dispersive X-ray spectroscopy; and Brunauer, Emmet, and Teller method.

Jun 7, 2022

By E. V. Manlapig, M. C. Harris

"The complexity of the flotation process has made the identification of an appropriate model structure for the predictive simulation of flotation circuits far from obvious. Work performed under the auspices of the AMIRA P9 flotation program has indicated that the metallurgical performance achieved from a flotation cell arises from the interaction of two essentially independent property classes, namely the cell operating conditions and the properties of the cell feed stream. These observations have led to the development of a model structure that associates a constant set of flotation parameters to the streams of the circuit, which are transformed into a flotation response depending on the operating conditions within the flotation cell.A variety of alternative model structures exist within the literature which do not make this distinction between cell and stream flotation properties, and many of these models are in widespread use for flotation optimisation and design studies, both in industry and academia.In this paper, circuit survey and laboratory batch flotation data collected from an industrial flotation circuit are analysed. The data demonstrate that streams in an industrial flotation circuit exhibit varying particle floatability – concentrate streams typically float faster than tailing streams (Figure 1(a)). This floatability, however, is generally conserved around the various units within the flotation process (i.e. the effective floatability of the combined feed and product streams of a unit is equivalent (Figure 1(b)))."

Jan 1, 2003

By E. V. Manlapig, M. C. Harris

"The complexity of the flotation process has made the identification of an appropriate model structure, for use in the prediction of flotation circuit performance, far from obvious. Work performed under the auspices of the AMIRA P9 flotation program has indicated that the metallurgical performance achieved from a flotation cell arises from the interaction of two essentially independent property classes, namely the cell operating conditions and the properties of the cell feed stream. These observations have led to the development of a model structure that associates a constant set of flotation parameters to the streams of the circuit, which are transformed into a flotation response depending on the operating conditions within the flotation cell.A variety of alternative model structures exist within the literature which do not make this distinction between cell and stream flotation properties, and many of these models are in widespread use for flotation optimisation and design studies, both in industry and academia.In this paper, data collected from an industrial flotation circuit is used to derive the parameters associated with two different types of flotation models. Simulations performed using these models demonstrate the need to differentiate between cell and feed properties. A model that does not differentiate between these two properties fails to successfully predict the metallurgical performance of a flotation circuit after a disturbance."

Jan 1, 2003

By Lisa Koch, Eleanor Martin

"Each underwater mining project is different. However, most have one thing in common: To be successful. We will draw on our experience advising hundreds of international clients each year on mining, offshore oil & gas and shipping matters to highlight some legal, commercial and practical issues to consider when structuring underwater mining projects. We will look at new ways of allocating risks and rewards in order to obtain much needed investment for underwater mining projects to commence both the exploration and exploitation phase.HighlightsRisk profileWe will look at a typical underwater mining project from the viewpoint of an investor and highlight some of the perceived risks, and potential mitigants.Contractual structureWe will analyse how the mining industry and oil & gas service industry have responded to low commodity prices to examine innovate contractual arrangements with suppliers and stakeholders, and how they can be tailored to the underwater mining industry. FinancingWe will explore some potential financing structures which could be relevant to the underwater mining industry."

Jan 1, 2017

By J Coombes

Within the mining industry there is a growing trend of placing inexperienced technical people into positions of responsibility beyond their readiness. Their responsibilities often include providing the fundamental basis for decision-making: the resource model or even the daily grade control estimates. Whilst software continues to make the processes more accessible, the thinking and rationale for selecting parameters still requires control rather than auto-piloting. Operators run these systems in virtual isolation, and have limited immediate access to experts. Beyond the stress of the professional burden are the increased risks to the mining operations and overall project success.While many experienced experts recall being thrown in the deep end, the relative isolation from experts coupled with the gravity of professional burden before readiness, is less familiar. Many recall in intimate detail the experts who gave them direction, assisted them along the way and even helped them claw out of inadvertent mistakes. Experienced professionals all have a responsibility to enable capability across the generations, to ease the burden and to mitigate the risks.This paper provides an outline of how mentoring as an on-the-job professional development process can be structured to more fully enable success of a mentoring program. Three examples complement the principles presented.CITATION:Coombes, J, 2012. Structuring meaningful mentoring, in Proceedings International Mine Management 2012, pp 15-22 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 20, 2012

By H. Bannach

"This paper focusses on what seem to be the leading indicators of prosperity in the minerals industry during this decade: the geographical distribution of deposits, environmental impact, capital allocation and acid consumption. There is a potential for meeting environmental criteria at a reasonable profit margin, but those with limited acid demand within economic range will face hard times to meet growing environmental concerns, resulting in additional mine closures. At the other end, those with old waste dumps who are thinking about smelting capacity additions will need capital influx at a much larger rate than ever before. All things considered, a change should be made in the way the world's copper reserves are computed, because there is a growing need to internalize these effects back to the ore blocks before a meaningful estimate of reserves becomes available.IntroductionThe copper industry has undergone several changes during the past decade, many of which were expected to take place because they rel1ect the economics of ageing mines. However, many others took place that shocked the industry because they were not completely under control. The focus of this paper is to rel1ect on those changes, and on market expectations for this decade that somehow depend on their impact.To review the prospects for new mine developments and expansions from an industry perspective to a full extent, it would be necessary to consider not only the deposits themselves, but also geographical constraints, environmental constraints, labour composition, technology development and use, the availability of capital, ownership issues, and integration within the industry. This paper, however, will concentrate on only some of the key elements that are believed to playa major role in shaping the market in the decade that has just begun. These elements, all interconnected, are:"

Jan 1, 1992

By K. -A. Björkstedt

INTRODUCTION Strassa lies in the central part of Bergslagen, a tradi¬tional mining district, on the eastern side of the Stora Valley at an elevation of about 200 m above sea level. A railway siding runs between the mine and the Stora railway station from which there are railway connections to the shipping port and iron and steel works in Oxelosund, about 224 km away. The distance to the provin¬cial capital Orebro is about 60 km. The climate is typi¬cal for this part of central Sweden and is illustrated by the diagram of monthly precipitation and temperatures for the years 1968-1975 (Fig. 1). HISTORY There is no certain information as to when the Strassa mine was first worked, but it is known from sur¬viving accounts of mine inspectors that there were smelt¬ing works in operation in nearby villages in the 12th century. An example is the Gusselhytta ore smelting works, 10 km south of Strassa, which dates from this period. Around the year 1540 there were two smelting works in Strassa, the Upper Karberg and Lower Karberg works. Ore for these smelters was probably taken from Strassa and from the adjacent Blanka mine. In the year 1624 Strassa is mentioned by the painter Jons Nils Krook in an account of the iron mines in the Linde mining district (Linde Bergslags Jarngruvor). Several mines were listed in the area, the deepest being about 30 m. An impressive power installation is mentioned in 1639, including a piston system of lashed poles for transmit¬ting power from the Stora River to the Strassa fields. Its length was 2670 m. Common ground comprising about 20.2 km2 (5000 acres) of forest was allocated in 1689 for the furtherance of mining operations. Until the beginning of this century only the rich cen¬tral parts of the ore body were mined and these yielded, after handpicking, lump ore suitable for smelter feed. An example of the ore grades from these early times is an analysis of ore from the "Big Mine" (Storgruvan) from the year 1873: 48.5% Fe, 0.008% P, and 0.06% S. This same year a total of about 18 000 t was ex¬tracted from the Strassa mine. OWNERSHIP The mine was owned and run until 1874 by a min¬ing association made up of 119 so-called "bergsman," who were homesteaders often engaged in agriculture and timber-cutting as well. In that year the Strossa Grufvebolag (Mining Co.) was founded. In 1906 it was con¬verted into a joint stock company, the Strossa Gruveaktiebolag. This was acquired in 1907 by Metallurgiska AB for the implementation of Gustav Grondal's beneficiating and briquetting methods, for which the Strassa ore was well suited. The same year saw the completion of a new ore dressing plant with an annual production of 46 000 t of ore concentrate. In 1911 the mine passed to new hands, and in 1913 it was purchased by an Austrian company. Extensive new installations were made and in 1915 a new dressing and briquetting plant was completed with twice the capacity of the old one. In 1917 the Strassa mine was acquired by Granges. Be¬cause of unfavorable business trends and technical diffi¬culties, mining operations were brought to a close in 1923. Pumping kept the mine free of water until 1933 but it was completely filled ten years later. Up to 1950 the surface buildings and installations remained intact but the large dressing and briquetting plant burned to the ground in that year. Today only the machine shop re¬mains from this earlier period of operation, now housing parts of the Mineral Processing Laboratory. The decision to take up mining operations again was made in 1955 and construction work began the follow¬ing year. Of the old installation, only the "southern shaft" could be used for some development drifting after it had been completed with a new headframe. Other¬wise, all the buildings and installations required for the operations had to be rebuilt. New installations ready by 1960 were office and personnel facilities, a new shaft and headframe, a sorting and concentrating plant, a macadam plant, settling basins, pump stations, and a railway and yard with transport equipment. The instal¬lation was completed with two plants

Jan 1, 1982

By Swaminathan Srinivasan, Jess A. Schroeder

"Landslide activity along U.S. 50 in Cincinnati, Ohio (USA) has caused roadway damage for decades. After a necessary closure of three lanes due to slope movements, emergency stabilization measures were undertaken to protect the roadway by providing a short-term solution necessitated by The Ohio Department of Transportation budget constraints. The landslide shear plane occurred on a sloping bedrock surface as much as 50 feet below grade. Drilled shafts were installed 40 feet downslope of the roadway shoulder and were heavily reinforced across the shear plane but steel reinforcing did not extend the full length of the shafts and was stopped well short of the ground surface. Instrumentation data has been collected for 11 years after construction has shown these “Stub Piers” have provided much more than a short-term solution and have provided an attractive alternate to conventional deep shafts or tieback drilled shaft options.INTRODUCTIONLandslide activity has occurred along U.S. Route 50 in western Cincinnati, Ohio for many decades. The site is located between North Bend and Addyston, Ohio on the right descending (cutting) bank of the Ohio River. Road distress caused by slope movements required periodic repairs over recent decades. Railroad tracks downslope of the roadway also showed signs of horizontal displacement and periodic repair. Visual evidence in 2005 suggested the shear plane extended below the US 50 roadway and extended out into the Ohio River.A weed and brush-covered slope extended down slope from the roadway at about 3H:1V for a vertical distance of about 20 feet. Above US 50, the hillside continued to rise more than 100 feet. There is a railroad right-of-way at the toe of the slope with the Ohio River bank just downslope of the railroad.In 2005, Terracon Consultants was retained by the Ohio Department of Transportation (ODOT) to perform a geotechnical study that included 17 test borings and inclinometer monitoring at 4 locations. Roadway damage was occurring (see Figure 1). After only a few weeks of monitoring, the inclinometer casings sheared off about 50 feet below grade, near the soil / bedrock interface (see Figure 2). Soon after, the roadway distress worsened, causing ODOT to close 3 of the 4 lanes to traffic and reroute traffic onto the remaining single lane and shoulder. Terracon was asked to develop a stabilization design under emergency repair conditions. However, both limited budget and time-related constraints necessitated a direction by ODOT that the solution be at least “pseudo” short-term (3 to 5 years)."

Jan 1, 2017

By Stuart Elliot

Brownfield project portfolios are notoriously hard to manage. Day to day there is a constant stream of changes and challenges within projects and across the whole program. When the budget year is over, we?re often left wondering: did the facilities get what they really needed? Did we get value for the capital that was spent? Did we get all the project control and process improvement that we paid for? Great work has been done over the years by the Project Management Institute, Construction Industry Institute and Independent Project Analysis to identify what leads to project success, develop project delivery systems and equip project leaders to perform better. But is attention to individual projects all we need when the job is to deliver a portfolio of many projects? Let?s work with an analogy for a moment, and say a project is like a car, and a project manager the driver. Why can?t all the projects in the portfolio get home in time for dinner? The answer, of course, is that the commute home is about traffic, not just about cars. The road, the signals and the actions of other drivers affect us in our individual cars. Optimizing traffic flow is not about managing individual cars, it is about creating the conditions that allow all traffic to move as smoothly as possible. When we?re stuck in traffic, it doesn?t really matter that we are skilled drivers who know our exact location and our engine?s vital signs. Success with a brownfield portfolio requires more than the equivalent of driver training and a good GPS in every vehicle. Managing the annual budget requires more than tight management of each project. This is not a suggestion to abandon project management in the brownfield multi-projects world; the idea is to find and apply the right tools for delivering a portfolio. Remember, we want confidence in 3 areas: 1. that the facility is getting what it really needs, when it needs it 2. that we are getting value for money invested in facility modifications and improvements, and 3. that our controls are adding value by guiding our improvement What are those portfolio tools? The job they have to do is distinct from project-level thinking: ? Create a clear and balanced business pull for project ideas ? Maintain a respectable plan for fiscal, resource and business control ? Organize the work into a steady flow ? Manage the nature and timing of value-driven project substitutions and priority changes ? Focus on overall business value added and best use of resources ? Repurpose the projects organization into being the way the facility gets improved

Nov 1, 2011

[Aalde, Kaare, ('40) New Mexico School of Mines, Socorro, N. M. Abadesco, Enrique A., ('39) Univ. of the Philippines, Manila, P. I. Abdul-Ahad, A., ('39) Montana School of Mines, Residence Hall, Butte, Mont. Abreu, Ovidio M., ('38) Univ. of Nevada, Reno, Nev. Acker, Voscoe, . ('39) Agricultural & Mech. College of Texas, College Station, Tex. Acosta S., Gonzalo, ('40) Univ. of Texas, Univ. Sta., Box 1785, Austin, Tex. Adams, Albert, ('38) New Mexico School of Mines, Socorro, N. M. Adams, Charles W.,' ('39) Michigan College of Min. & Tech., Houghton, Mich. Adams, Hugh T., Jr., ('39) Univ. of Oklahoma, Norman, Okla. Adams, Jack L., ('39) Univ. of Oklahoma, Norman Okla.]

Jan 1, 1940

[Abrahamson, Guy C., (5'43) Lt., 0-880861, Hammer Field Fresno Calif. Adamec, LAW, (8'42) c/o Braden Copper Co., Rancagua, Chile. Adams, Karl S., (9'43) Univ. of New Hampshire, Durham, N. H. Agnilar, Roperto Q., (9'43) Texas College of Mines, El Paso Texas. Ainge, B'onald Farra, (943) Otago University, Dunedin, New Zealand. Akaran, Cevdet A,, (9'44) Pennsylvania State College, State College, Pa. Albala, Americo, (5'44) School of Mineral Industries, The Pennsylvania State College, State College, PA.]

Jan 1, 1946

Abdul-Ahad. A., Student, Montana School of Mines, Residence Hall Butte, Mont. '39 Abramovits, Charles, Student, Case School of Applied Science Cleveland, Ohio. '37 Abreu, Ovidio M., Student, Univ. of Nevada Reno, Nev. '38 Acker, Voscoe, Student, Agricultural & Mech. College of Texas College Station, Tex. '39 Adams, Albert, Student, New Mexico School of Mines Socorro. N. M. '38 Adams, Charles W., Student, Michigan College of Min. & Tech Houghton, Mich. '39 Adams, Hugh T., Jr., Student, Univ, of Oklahoma Norman, Okla. '39 Adams, Jack L., Student, Univ. of Oklahoma Norman, Okla. '39 Adams, Jack M., Student, Univ of Alaska College, Alaska. '39 Adams, Lewis J., Student, Agricultural & Mech. College of Texas, Box 2514, College Station, Tex. '39 Adams, Robert E., Research Engr., Battelle Memorial Inst Columbus, Ohio. '38 Adamson, George M., Jr.. Student, Univ. of Utah Salt Lake City, Utah. '39 Adkisson, J. F., Jr., Student, Agricultural & Mech. College of Texas, Box 1003, College Station. Tex. '38

Jan 1, 1939

Abbott, Argyle Campbell 1209 Sherwin Ave., Chicago, Ill. Almstrom, Adne A., Student, Met. Engrg., Washington State College Pullman, Wash. Ankudinoff, N., School of Mines, Univ. of Utah Salt Lake Cite, Utah. Apter, Robert F., Student, McGill Univ Montreal, Que., Canada. Bailey, Donald G 798 Kensington Rd., Los Angeles, Cal. Baker, Kenneth B., Met., Aluminum Co. of America Pittsburgh, Pa. Barger, Thomas, Student, Univ. of North Dakota Grand Forks, N. D. Bartholomees, Geo. C Box 304, Bonne Terre, Mo. Bates, Walter, Student, Univ. of Utah, School of Mines Salt Lake Cite, Utah. Bobb, Russell V 16 College Ave., Houghton, Mich. Boswell, John C., Stripping Asst., Fairbanks Exploration Co Fairbanks, Alaska. Brandenburg, E. C., Student, Univ. of Kentucky 112 Church St., Lexington, Ky. Brannen, John, Chemist, Assay Office, Consolidated Min. & Smelt. Co. of Canada, Ltd., Tadanac, B. C., Canada. Brooker, Edgar, Jr., Student, Ferrous Met., Stanford Univ., Stanford University, Cal. Brooking, Leslie E 738 Lakoma, Norman, Okla. Clark, Martin Lester, Student, Missouri School of Mines Rolla, Mo. Collins, Edward D., Jr Box 1597, Ribbing, Minn. Comeau, Faye Bernard, Student, New Mexico State School of Mines Socorro, N. M. Conder, Henry S., Student, Pet. Engrg., College of Min., Univ. of California, Berkeley, Cal. Cotton, John Francis, Metallographist, Stealton Plant, Bethlehem Steel Corp., Steelton. Pa. Dahlgren, Elmer George, Student, Univ. of Wisconsin, Tripp Hall, Madison, Wis. Dale, James L., Student, Colorado School of Mines Golden, Colo. Dashti, Mirza Abdullah Khan, Graduate Student, Columbia School of Mines, Engrg. Chemistry, New York, N. Y. DeHuff, Gilbert L., Jr., Student, Lehigh Univ Bethlehem, Pa. de Romana, Enrique P., Jr. Engr Casilla 22, Arequipa, Peru. Oresbach, Charles Howard, Geol., Gulf Production Co Box 1428, Amarillo, Tex. Evens, Howard G., Student, Michigan College of Min. & Tech Houghton. Mich. Fassler, Glen Emerson Rodman, Inspiration, Ariz. Feight, Charles Donald, Foreman, Clairton By-Product Coke Wks., Carnegie Steel Co., 319 5th St., Wilson, Pa. Floe, Carl F., Student, State College of Washington Pullman, Wash. Fuentes, Vicente, Student, Pet. Engrg., Univ. of Oklahoma, School of Mines, Norman, Okla. Fuhrman, Carl F., Student, New Mexico School of Mines Socorro, N. M. Goergen, Gerald G., Cerro de Pasco Copper Corp Casapalca, Peru. Grove, Hubert A., Training Course, U. S. Aluminum Co New Kensington, Pa. Gastetter, Robert E 1010 N. Cherry Ave., Tucson, Ariz. Halbouty, M. T., Student, Texas Agriculturcl & Mech. College, Box 254, Faculty Exchange, College Station, Tex. Halfast, Edgar 710 E. Okmulgee Ave., Muskogee, Okla. Hall, Robert Lee 121 58th St., Niagara Falls, N. Y. Hanson, Rolf H., Student, Colorado School of Mines Golden, Colo. Hillyer. Shaler G., Student, New Mexico School of Mines Socorro, N. M. Hoertel, Frederick W., Met., R. W. Hunt Co., Engrs St. Louis, Mo. Holtz, Henry G., Student, Ohio State Univ Columbus, Ohio. Hon, Richard J Box 721, Miami, Ariz. Huffman, James O'Neil, Student, College of Min., Univ. of California Berkeley, Cal.

Jan 1, 1929

Adams, Bernard, Student, South Dakota School of Mines. Rapid City, S. D. '30 Ahlskog, Harold A., Student, Washington State College Pullman, Wash. '30 Aldridge, John, Student, New Mexico School of Mines Socorro, N M. '30 Almstrom, Adne A., Student, Met. Engrg., Washington State College Pullman, Wash. '29 Ancell, Virgil F., Student, Missouri School of Mines Rolla, Mo. '30 Ankudinoff, N., Mill Draftsman, Arthur G McKee & (:o., 2422 Euclid Ave., Cleveland, Ohio. '30 Apablasa, Salvador C., Student, Univ. of California Los Angeles, Cal. '31 Armstrong, Robert H., Student, Lafayette College Easton, Pa. '31 Armstrong, Thomas E., Student, Univ. of California Los Angeles, Cal '31 Aud, Robert A., Student, Lafayette College Easton, Pa. '30 Backus, Robert Small, Student, Mass.- Inst. of Tech . Cambridge, Mass. '30 Bailey, William C., Student, Univ. of California Los Angeles, Cal '30 Banning, Lloyd H., Student, South Dakota State School of Mines Rapid City, S D. '81 Barclay, M. G., Student, Colorado School of Mines Golden, Colo. '30 Barger, Thomas, Student, Univ. of North Dakota Grand Forks, N. D. '29 Barker, C. L., Student, Colorado School of Mines Golden, Colo. '30 Barker, Edgar Morgan. Student, Univ. of Utah Salt Lake City, Utah. '31 Barnwell, Earl E., Student, Oregon State College. Corvallis, Ore. '30 Bartholomees, Geo. C Box 304, Bonne Terre, Mo. '29 Bartholomees, Louis P., Student, Colorado School of Mines Golden, Colo. '30 Bary, Robert L., Student, Univ. of Kansas Lawrence, Kans. '30 Basham, Lester G., Student, South Dakota School of Mines Rapid City, S D. '31 Bates, Walter H., Student, School of Mines, Univ. of Utah .. Salt Lake City, Utah. '30 Beardshear, George T., Student, South Dakota State School of Mines.Rapid City, S D. '31

Jan 1, 1923

[Abrahamson, Guy C., (5'43) 1st Lt., A.C., 0-880861, Base Weather Sta., Fairfeld-Suisun AAB, Suisun, Calif. Adam, Howard Wilbur, (S'46) 45 Eaton Ave., Woburn, Mass. Aguilar, Ruperto G., (S'43) Texas College of Mines, El Paso, Texas. Ainge, Ronald Farra, (S'43) Otago University, Dunedin, New Zealand. Albala, Américo, (S'44) Casilla 4106, Santiago, Chile. Albrecht, Theodore J„ (S'42) Pfc., Co. F, Syme Hall, Rm. 1, SCU 3421, ASTP, N. C. State College, Raleigh, N. C. Aldridge, E. E., Jr., (S'39) Box 58, Eagle Pass, Texas. Alfred, Robert M., (S'40) 25 South St., Brighton, Mass. Allan, Douglas H. W., (S'40) 460 Main St., E., Hamilton. Ont.. Canada.]

Jan 1, 1946

Aaby, Alton O , (S'47) Univ of Minnesota, Mimeapolis, Minn Aaby, Waldo S , (S?48) Univ of Minnesota, Minneapolis Minn Aalde, Kaare, (S'48) Univ of Nevada, Reno, Nev Aaring, Floyd D , (S'48) Univ of Oklahoma, Nor man, Oka Aaronson, Hubert I , (S'47) Carnegie Inst of Technology, Pittsburgh, Pa Abbott, Peyton Osborn, (S'46) 1502 Westover, Austin 21, Texas Abel, Malcolm D , (S'47) Univ of Texas, Austin, Texas Aberg, Richard S , (S'47) Univ of Minnesota, Minneipolis, Minn Abrahamson, Guy C , (S'43) 420 W Dennis St , Wilmington, Calif Abrahao, Benjamin, (S'46) Escola Politeenica da Unnersidade, de Sin Piulo, Braizil Achter, Meyer R , (S'46) Carnegie Inst of Tech , Pittsburgh, Pa

Jan 1, 1952